Comparison of pregnancy outcomes among patients of different ages who underwent frozen-thawed high-quality single blastocyst transfer.

OBJECTIVE: To investigate the feasibility of performing frozen-thawed high-quality single blastocyst transfer in women of different ages. METHODS: A total of 1,279 women were divided into four groups: a 38-40-year-old group (n = 147), 35-37-year-old group (n = 164), 30-34-year-old group (n = 483), and < 30-year-old group (n = 485). Intergroup comparisons of baseline characteristics and pregnancy and neonatal outcomes were made. RESULTS: The clinical pregnancy rate (47.6%), and live birth rate (34.0%) in the 38-40-year-old group were significantly lower than those in the 30-34-year-old group (64.4%, 50.9%, respectively; all P < 0.001) and < 30-year-old group (62.9%, 50.7%, respectively; all P < 0.001). However, the 35-37-year-old group did not differ from the other three groups in these two dimensions (all P > 0.05). Moreover, there were no differences in the rates of biochemical pregnancy, miscarriage, or obstetric or neonatal complications among the four groups (all P > 0.05). According to the multivariate logistic regression analysis, the 35-37-year-old group was not associated with non-live birth outcomes, adverse pregnancy outcomes, or obstetric or neonatal complications. However, being 38-40 years of age was a risk factor for non-live birth (OR = 2.121, 95% CI: 1.233-3.647) and adverse pregnancy outcomes (OR = 1.630, 95% CI: 1.010-2.633). Post hoc power analysis showed that the study was sufficiently powered to detect meaningful differences. CONCLUSION: Frozen-thawed high-quality single blastocyst transfer produces the same satisfactory pregnancy outcomes for women aged 35-37 years as younger patients. Future prospective randomized controlled studies with larger populations are needed to verify the feasibility and safety of this method.

IGF2BP2 promotes lncRNA DANCR stability mediated glycolysis and affects the progression of FLT3-ITD + acute myeloid leukemia.

Internal tandem duplication (ITD) is the most common type of FLT3 mutation (FLT3-ITD), accounting for about 25% of AML patients. The expression of DANCR in FLT3-ITD AML had not been paid attention to, and whether its regulatory relationship with IGF2BP2 can affect the progression of FLT3-ITD AML was unclear. Our study sought to verify the biological role of IGF2BP2 as an m6A reading protein in FLT3-ITD AML. To further explore the role and mechanism of DANCR in AML, and provide a basis for the screening of biomarkers and the development of targeted drugs. The results show that IGF2BP2 was upregulated in FLT3-ITD+ AML patients and cells. Si-IGF2BP2 could inhibit the proliferation, glycolytic and promote the apoptosis in MV4-11 cells. IGF2BP2 could promote the DANCR RNA stability. This discovery will provide new horizons for early screening and targeted therapy of FLT3-ITD+ AML.

Derivation and validation of a novel score for early prediction of severe CRS after CAR-T therapy in haematological malignancy patients: A multi-centre study.

Chimeric antigen receptor T (CAR-T) cell therapy is highly effective in inducing complete remission in haematological malignancies. Severe cytokine release syndrome (CRS) is the most significant and life-threatening adverse effect of this therapy. This multi-centre study was conducted at six hospitals in China. The training cohort included 87 patients with multiple myeloma (MM), an external validation cohort of 59 patients with MM and another external validation cohort of 68 patients with acute lymphoblastic leukaemia (ALL) or non-Hodgkin lymphoma (NHL). The levels of 45 cytokines on days 1-2 after CAR-T cell infusion and clinical characteristics of patients were used to develop the nomogram. A nomogram was developed, including CX3CL1, GZMB, IL4, IL6 and PDGFAA. Based on the training cohort, the nomogram had a bias-corrected AUC of 0.876 (95% CI = 0.871-0.882) for predicting severe CRS. The AUC was stable in both external validation cohorts (MM, AUC = 0.907, 95% CI = 0.899-0.916; ALL/NHL, AUC = 0.908, 95% CI = 0.903-0.913). The calibration plots (apparent and bias-corrected) overlapped with the ideal line in all cohorts. We developed a nomogram that can predict which patients are likely to develop severe CRS before they become critically ill, improving our understanding of CRS biology, and may guide future cytokine-directed therapies.

A distinct cytokine network distinguishes chimeric antigen receptor T cell (CAR-T)-associated hemophagocytic lymphohistiocytosis-like toxicity (carHLH) from severe cytokine release syndrome following CAR-T therapy.

BACKGROUND AIMS: With the increasing application of chimeric antigen receptor (CAR)-T cell therapy in various malignancies, an extra toxicity profile has been revealed, including a severe complication resembling hemophagocytic lymphohistiocytosis (HLH), which is usually disguised by severe cytokine release syndrome (CRS). METHODS: In a clinical trial in whom 99 patients received B-cell maturation antigen CAR-T cells, we identified 20 (20.20%) cases of CAR-T cell-associated HLH (carHLH), most of whom possessed a background of severe CRS (grade ≥3). The overlapping features of carHLH and severe CRS attracted us to further explore the differences between them. RESULTS: We showed that carHLH can be distinguished by extreme elevation of interferon-γ, granzyme B, interleukin-1RA and interleukin-10, which can be informative in developing prevention and management strategies of this toxicity. Moreover, we developed a predictive model of carHLH with a mean area under the curve of 0.81 ± 0.07, incorporating serum lactate dehydrogenase at day 6 post-CRS and serum fibrinogen at day 3 post-CRS. CONCLUSIONS: The incidence of carHLH in CAR-T recipients might be relatively higher than we previously thought. relatively higher than we previously. A cytokine network distinguished from CRS is responsible for carHLH. And corresponding cytokine-directed therapies, especially targeting IL-10, are worth trying.

Association between different insulin resistance surrogates and infertility in reproductive-aged females.

BACKGROUND: Obesity and metabolic syndrome are observed more frequently in infertile women, and insulin resistance (IR) is closely related to them. However, there are no studies that have examined the association between different IR surrogates and female infertility, hence we investigated the potential association between them in the general population. METHODS: This was a cross-sectional study using data from the National Health and Nutrition Examination Survey (NHANES, 2013-2018). The association of different IR surrogates (HOMA-IR index, TyG index and TyG-BMI index) with female infertility was estimated by multivariable regression analysis. RESULTS: After adjusting for confounders, the HOMA-IR index and TyG index did not show an association with female infertility, while the TyG-BMI index was found to have a positive association with female infertility (OR = 1.01, 95% CI: 1.00, 1.01; P < 0.0001), and the OR of the TyG-BMI group T3 (≥ 255.55) was significantly different compared to the group T1 (< 185.31) (OR = 3.02, 95% CI: 1.62, 5.60). Similar results were seen in most of the subgroup participants by stratified analysis (P-interaction > 0.05). However, different IR surrogates did not show variability in their ability to predict infertility [TyG-BMI: 0.68 (95% CI: 0.62, 0.74) vs. TyG: 0.62 (95% CI: 0.57, 0.68) vs. HOMA-IR: 0.65 (95% CI: 0.60, 0.71)]. CONCLUSIONS: Our result suggests that high levels of TyG-BMI index were positively associated with female infertility in US reproductive-aged females.

Investigate the effect of COVID-19 inactivated vaccine on sperm parameters and embryo quality in in vitro fertilization.

Since the reproductive toxicity of COVID-19 vaccines have not been assessed in previous clinical trials, and studies have shown that SARS-CoV-2 is associated with a decrease in sperm parameters. Although it has been reported that the mRNA SARS-CoV-2 vaccines do not adversely affect semen parameters, whether this conclusion applies to inactivated vaccines remains unclear. Here, we conducted a study among patients who accepted in vitro fertilization (IVF) at the reproductive centre between June and August of 2021. In the enrolled cases, men who have completed two doses of COVID-19 inactivated vaccine were included in "vaccine group" (N = 105), and those who were not vaccinated were included in "control group" (N = 155). In this study, we compare the sperm parameters and embryo quality between these two groups. Our data showed that the sperm parameters were similar in terms of volume, sperm concentration, sperm count, progressive motility, total motility and total motile sperm count between these two groups. Similarly, no significant differences were observed in IVF outcomes. The mean number of 2PN, cleavage-stage embryos, blastocysts, and good-quality blastocysts was 8.59 ± 4.47, 5.06 ± 3.17 and 2.08 ± 1.79 in vaccine group, 7.75 ± 4.14, 4.34 ± 3.06 and 1.74 ± 1.54 in control group, respectively. The high-quality blastocyst rate was 41.05% (218 of 531) in vaccine group and 40.03% (269 of 672) in control group (p > 0.05). In addition, no differences were observed in biochemical and clinical pregnancy rates between the two groups. In summary, our results revealed that COVID-19 inactivated vaccine administration exhibited no negative effect on sperm parameters and embryo quality in IVF.

Effect of EPA on Hsp90 and GRα protein expression in multiple myeloma drug-resistant cells.

BACKGROUND: Approximately 20% of MM patients harbor glucocorticoid (GC) resistance and are not responsive to therapeutic effect. Chaperoneheat-shock proteins Hsp90 is needed for ligand docking, The imbalance of Hsp90/GRα (glucocorticoid receptor α) may be an important cause of GC resistance. Recent studies have indicated that EPA could repress cancer cell growth by regulating critical influential factors in progression of cancer, consisting of resistance to drugs, chemosensitivity. The aim of the present study was to test the cytotoxic effects of EPA alone or EPA + Dexamethasone in dexamethasone-resistant MM cell (MM.1R) and investigate whether DHA can induce apoptosis and reverse acquired glucocorticoid resistance in dexamethasone-resistant MM cell (MM.1R). METHODS: Cell Counting Kit-8 (CCK-8) was used to detect the proliferation of MM.1R cells after treating with EPA alone and EPA combined with DEX. Mitochondrial membrane potential was measured by flow cytometry and GRα and Hsp90 protein expression were assessed by western blot analysis. RESULTS: EPA alone was able to inhibit cell proliferation as evidenced by CCK-8 assay and the tumor growth was remarkably suppressed by EPA + Dexamethasone, Cell apoptosis after EPA treatment was obviously observed by Flow cytometry analysis of the mitochondrial membrane potential. Analysis of Hsp90 and GRα proteins in MM.1R cells incubated with EPA revealed down-regulation of Hsp90 and up-regulation of GRα. Accordingly, the Hsp90/GRα ratio was significantly decreased with the increase of EPA concentration. CONCLUSIONS: EPA might be used as a new effective treatment for reversal of glucocorticoid-resistance in multiple myeloma.

Adiponectin signals through Adiponectin Receptor 1 to reverse imatinib resistance in K562 human chronic myeloid leukemia cells.

Adiponectin, a member of adipokines, is a functional ligand for Adiponectin Receptor-1 (AdipoR1) and Adiponectin Receptor-2 (AdipoR2), and has been found to be linked to the risk of CML. Imatinib has undoubtedly revolutionised the management and outcome of chronic myeloid leukemia (CML), however imatinib resistance has been recognized as a major problem in CML therapy. In this study, we first established imatinib-resistant K562 CML cells, and then evaluated the effect of Adiponectin in reversing imatinib resistance. The data presented here demonstrated that Adiponectin was able to reverse K562 resistance to imatinib in vitro and in vivo. Additional data with molecular approaches suggested that the reversion of Adiponectin in imatinib resistance signals through AdipoR1 but not AdipoR2 to downregulate Bcr-Abl expression and effect in imatinib-resistant K562 CML cells. Taken together, our data showed that Adiponectin can reverse imatinib resistance in CML, and to a certain extent elucidate the mechanism of Adiponectin reversing imatinib resistance that may provide a new and promising approach in imatinib resistance management in CML therapy.

Enhancing effect of ß-elemene emulsion on chemotherapy with harringtonine, aclacinomycin, and Ara-c in treatment of refractory/relapsed acute myeloid leukemia.

Objective : This study is to determine the curative effect of ß-elemene emulsion on chemotherapy in the treatment of refractory/relapsed acute myeloid leukemia (AML). Methods : In the ß-elemene emulsion plus HAA chemotherapy (harringtonine, aclacinomycin, Ara-c group) group, 120 cases received ß-elemene emulsion (400 mg) plus the HAA treatment. A 14-day treatment was a course of treatment, followed by an 8-14 day pause, and then the next course of treatment. The HAA treatment included Ara-C, 100 mg/m2, once every 12 h from day 1 to day 7; aclacinomycin, 20 mg/m2, from day 1 to day 7; and homoharringtonine, 4 mg/m2, from day 1 to day 7. The patients in the control HAA group received HAA treatment only. For both groups, effective antibiotics were given to patients when it was necessary. Results : The total effective rate in the ß-elemene emulsion plus HAA group was 80.8%. But the total effective rate in the HAA only group was 52.9%. These results suggest that the ß-elemene emulsion plus HAA treatment has a much better curative effect in comparison with the HAA only treatment (P < 0.05). Furthermore, ß-elemene emulsion has slightly adverse response, without causing blood and bone marrow depression. Conclusion : ß-elemene emulsion has a curative effect in treatment of refractory/relapsed AML in combination with harringtonine, aclacinomycin, and Ara-c.

Coexistence of hereditary spherocytosis with SPTB P.Trp1150 gene variant and Gilbert syndrome: A case report and literature review.

A congenital protein anomaly in the erythrocyte membrane skeleton causes a hereditary haemolytic illness known as hereditary spherocytosis (HS). The primary characteristic of HS is an increase in the number of tiny spherical red blood cells in the peripheral blood. The chief clinical features of HS include anaemia, jaundice, splenomegaly, spherical erythrocytosis in the blood, chronic anaemia with haemolysis, and recurrent acute attacks. Most patients have a family history; some have autosomal recessive inheritance, whereas most have autosomal dominant inheritance. In cases of severe hyperbilirubinemia disproportionate to haemolysis, other causes of hyperbilirubinemia should be considered. Gilbert syndrome (GS) is an autosomal dominant illness caused by the reduced activity of uridine diphosphate-glucuronosyl transferase lAl and is characterised by intermittent hyperbilirubinemia without any other signs or symptoms of liver disease. The possibility of the coexistence of HS and GS is very limited. Here we present the case of an elderly man with yellow skin and sclera recurring anaemia, and a final diagnosis of coexisting HS and GS.

Prenatal maternal inactivated COVID-19 vaccination: the maternal and neonatal outcomes, a retrospective cohort study.

Background: Despite the widespread adoption of COVID-19 vaccination, a comprehensive understanding of potential vaccine-induced adverse effects, particularly in the context of pregnancy, remains a critical area of investigation. Elevated concerns surround the maternal and neonatal outcomes subsequent to prenatal maternal COVID-19 vaccination. While existing studies have provided insights into the safety profile of COVID-19 mRNA vaccines, the extrapolation of these conclusions to inactivated COVID-19 vaccines poses uncertainties. Notably, limited data are available regarding the maternal and neonatal effects associated with inactivated COVID-19 vaccines. Objective: To evaluate the prenatal maternal inactivated COVID-19 vaccination and the impact on maternal and neonatal outcomes. Methods: This was a retrospective cohort study of women who delivered between January and June 2022 at a single university-affiliated hospital. Those who have completed at least one dose of inactivated vaccine before or during pregnancy were included in "vaccinated group," and those who were not vaccinated were included in "unvaccinated group," the maternal, pregnancy and neonatal outcomes were evaluated. Propensity score matching (PSM) was performed to balance the baseline parameters of the two groups. Results: A total of 1926 women were enrolled in this study, 827 (42.94%) women were prenatally vaccinated, and 1099 (57.06%) unvaccinated. The gestational week of delivery were slightly lower in the vaccinated group, 38.61 ± 1.89 weeks in the vaccinated group and 38.93 ± 1.49 weeks in the unvaccinated group. There was a higher rate of overall preterm delivery in the vaccinated group (aOR 1.61, 95% CI 1.07-2.42; p = 0.02), however, the probability of delivery before 34 weeks and before 32 weeks (early preterm delivery) were similar (p > 0.05). A total of 2009 infants were born, 851 in the vaccinated group and 1158 in the unvaccinated group. There were similar neonatal outcomes in the two groups. Conclusion: Although we found a slightly lower gestational week of delivery and a possible increased rate of late preterm birth in the vaccination group, there was no difference in mean neonatal weight, incidence of low birth weight infants and other neonatal adverse complications. Meanwhile, there was no difference in pregnancy and maternal outcomes between the two groups.

Automated customization of large-scale spiking network models to neuronal population activity.

Understanding brain function is facilitated by constructing computational models that accurately reproduce aspects of brain activity. Networks of spiking neurons capture the underlying biophysics of neuronal circuits, yet their activity's dependence on model parameters is notoriously complex. As a result, heuristic methods have been used to configure spiking network models, which can lead to an inability to discover activity regimes complex enough to match large-scale neuronal recordings. Here we propose an automatic procedure, Spiking Network Optimization using Population Statistics (SNOPS), to customize spiking network models that reproduce the population-wide covariability of large-scale neuronal recordings. We first confirmed that SNOPS accurately recovers simulated neural activity statistics. Then, we applied SNOPS to recordings in macaque visual and prefrontal cortices and discovered previously unknown limitations of spiking network models. Taken together, SNOPS can guide the development of network models, thereby enabling deeper insight into how networks of neurons give rise to brain function.

PLAU promotes growth and attenuates cisplatin chemosensitivity in ARID1A-depleted non-small cell lung cancer through interaction with TM4SF1.

Loss of ARID1A, a subunit of the SWI/SNF chromatin remodeling complex, contributes to malignant progression in multiple cancers including non-small cell lung cancer (NSCLC). In the search for key genes mediating the aggressive phenotype caused by ARID1A loss, we analyzed 3 Gene Expression Omnibus (GEO) datasets that contain RNA sequencing data from ARID1A-depleted cancer cells. PLAU was identified as a common gene that was induced in different cancer cells upon ARID1A depletion. Overexpression of PLAU positively modulated NSCLC cell growth, colony formation, cisplatin resistance, and survival under serum deprivation. Moreover, enforced expression of PLAU enhanced tumorigenesis of NSCLC cells in nude mice. Mechanistically, PLAU interacted with TM4SF1 to promote the activation of Akt signaling. TM4SF1-overexpressing NSCLC cells resembled those with PLAU overepxression. Knockdown of TM4SF1 inhibited the growth and survival and increased cisplatin sensitivity in NSCLC cells. The interaction between PLAU and TM4SF1 led to the activation of Akt signaling that endowed ARID1A-depleted NSCLC cells with aggressive properties. In addition, treatment with anti-TM4SF1 neutralizing antibody reduced the growth, cisplatin resistance, and tumorigenesis of ARID1A-depleted NSCLC cells. Taken together, PLAU serves as a target gene of ARID1A and promotes NSCLC growth, survival, and cisplatin resistance by stabilizing TM4SF1. Targeting TM4SF1 may be a promising therapeutic strategy for ARID1A-mutated NSCLC.

Cytokine-based models for efficient differentiation between infection and cytokine release syndrome in patients with hematological malignancies.

Although the efficacy of chimeric antigen receptor (CAR)-T cell therapy has been widely demonstrated, its clinical application is hampered by the complexity and fatality of its side effects. Cytokine release syndrome (CRS) is the most common toxicity following CAR-T cell infusion, and its symptoms substantially overlap with those of infection. Whereas, current diagnostic techniques for infections are time-consuming and not highly sensitive. Thus, we are aiming to develop feasible and efficient models to optimize the differential diagnosis in clinical practice. This study included 191 febrile patients from our center, including 85 with CRS-related fever and 106 with infectious fever. By leveraging the serum cytokine profile at the peak of fever, we generated differential models using a classification tree algorithm and a stepwise logistic regression analysis, respectively. The first model utilized three cytokines (IFN-ß, CXCL1, and CXCL10) and demonstrated high sensitivity (90% training, 100% validation) and specificity (98.44% training, 90.48% validation) levels. The five-cytokine model (CXCL10, CCL19, IL-4, VEGF, and CCL20) also showed high sensitivity (91.67% training, 95.65% validation) and specificity (98.44% training, 100% validation). These feasible and accurate differentiation models may prompt early diagnosis of infections during immune therapy, allowing for early and appropriate intervention.

Dose-response association between 24-hour total movement activity and testosterone deficiency in adult males.

Background and objectives: Previous studies on the relationship between physical activity and testosterone are limited and controversial. Hence we investigated whether high level of physical activity is associated with a low risk of testosterone deficiency (TD). Methods: This cross-sectional analysis was conducted in a representative sample of US adult males who participated in the 2011-2014 cycle of the National Health and Nutrition Examination Survey (NHANES). We used the monitor independent movement summary (MIMS) to assess activity intensity, a novel physical activity metrics developed using raw data collected by accelerometers. Multivariable regression and smooth curve fitting was used to describe the relationships between physical activity and TD, and segmented regression model were used to analyze the threshold effect between them. Sensitivity analysis was conducted using interaction and stratified analysis. Results: A U-shaped relationship between daily MIMS units and risk of TD was observed. The optimal value of daily MIMS units for the lowest risk of TD was 14.77 (×103), the risk of TD decreased by 5% in patients per unit increase of daily MIMS units when daily MIMS units <14.77 (×103) (adjusted OR = 0.95, 95%CI: 0.91, 0.99), but increased by 12% per unit increase of daily MIMS units when daily MIMS units ≥14.77 (×103) (adjusted OR = 1.12, 95%CI: 1.01, 1.23). In sensitivity analyses, the threshold effect was also similar according to baseline characteristics (P-interaction >0.05). Conclusion: In a nationally representative sample of US adult males, light to moderate intensity physical activity is associated with a lower odds of TD, while high-intensity physical activity is associated with a higher risk of TD.

Transferable Adaptive Differential Evolution for Many-Task Optimization.

The evolutionary multitask optimization (EMTO) algorithm is a promising approach to solve many-task optimization problems (MaTOPs), in which similarity measurement and knowledge transfer (KT) are two key issues. Many existing EMTO algorithms estimate the similarity of population distribution to select a set of similar tasks and then perform KT by simply mixing individuals among the selected tasks. However, these methods may be less effective when the global optima of the tasks greatly differ from each other. Therefore, this article proposes to consider a new kind of similarity, namely, shift invariance, between tasks. The shift invariance is defined that the two tasks are similar after linear shift transformation on both the search space and the objective space. To identify and utilize the shift invariance between tasks, a two-stage transferable adaptive differential evolution (TRADE) algorithm is proposed. In the first evolution stage, a task representation strategy is proposed to represent each task by a vector that embeds the evolution information. Then, a task grouping strategy is proposed to group the similar (i.e., shift invariant) tasks into the same group while the dissimilar tasks into different groups. In the second evolution stage, a novel successful evolution experience transfer method is proposed to adaptively utilize the suitable parameters by transferring successful parameters among similar tasks within the same group. Comprehensive experiments are carried out on two representative MaTOP benchmarks with a total of 16 instances and a real-world application. The comparative results show that the proposed TRADE is superior to some state-of-the-art EMTO algorithms and single-task optimization algorithms.

A negative association between triglyceride glucose-body mass index and testosterone in adult males: a cross-sectional study.

Background and objectives: Insulin resistance (IR) is closely related to the decline or deficiency of testosterone in males. Triglyceride glucose-body mass (TyG-BMI) is considered to be a novel indicator of IR. We conducted this analysis to investigate the association between TyG-BMI and male testosterone, and to explore whether its ability to predict testosterone deficiency is superior to HOMA-IR and TyG. Methods: This was a cross-sectional study using data from the National Health and Nutrition Examination Survey (NHANES, 2011-2016). The TyG-BMI index was calculated from serum triglyceride, fasting plasma glucose and BMI. The association of TyG-BMI with male testosterone was estimated by weighted multivariable regression. Results: We included 3394 participants for the final analysis. After adjusting for confounders, TyG-BMI was found to show an independent negative association with testosterone (ß=-1.12, 95%CI: -1.50, -0.75, P<0.0001). Multivariate-adjusted beta also showed testosterone levels were significantly lower in the two highest TyG-BMI group (Q3, Q4) compared to the lowest group (Q1). Similar results were seen in all of the subgroup populations by stratified analysis (all P-interaction >0.05). Furthermore, ROC curve analysis indicated that the area under the curve of TyG-BMI index (0.73, 95% CI: 0.71, 0.75) was larger than that of HOMA-IR index (0.71, 95% CI: 0.69, 0.73) and TyG index (0.66, 95% CI: 0.64, 0.68). Conclusion: Our result suggested a negative association between TyG-BMI index and testosterone in adult males. The predictability of the TyG-BMI index for testosterone deficiency is better than that of HOMA-IR index and TyG index.

Automated customization of large-scale spiking network models to neuronal population activity.

Understanding brain function is facilitated by constructing computational models that accurately reproduce aspects of brain activity. Networks of spiking neurons capture the underlying biophysics of neuronal circuits, yet the dependence of their activity on model parameters is notoriously complex. As a result, heuristic methods have been used to configure spiking network models, which can lead to an inability to discover activity regimes complex enough to match large-scale neuronal recordings. Here we propose an automatic procedure, Spiking Network Optimization using Population Statistics (SNOPS), to customize spiking network models that reproduce the population-wide covariability of large-scale neuronal recordings. We first confirmed that SNOPS accurately recovers simulated neural activity statistics. Then, we applied SNOPS to recordings in macaque visual and prefrontal cortices and discovered previously unknown limitations of spiking network models. Taken together, SNOPS can guide the development of network models and thereby enable deeper insight into how networks of neurons give rise to brain function.

METTL3 affects FLT3-ITD+ acute myeloid leukemia by mediating autophagy by regulating PSMA3-AS1 stability.

The study was designed to explore the role of PSMA3-AS1 in initiation and progression of acute myeloid leukemia (AML) and investigate its action mechanism. Expression of PSMA3-AS1, miR-20a-5p and ATG16L1 both in vitro and in vivo was measured by qRT-PCR. The expression of protein was detected by western blot assay. Edu staining and flow cytometry were utilized to measure cell proliferation and apoptosis. Potential target was predicted by bioinformatics and was verified by dual-luciferase report gene assay and RNA pull down assay. QRT-PCR was used to quantify autophagy (LC3, Beclin1, P62) related genes. The m6A modification test is used to verify the effect of METTL3 on PSMA3-AS1. Tumor model was used to identify the effect of PSMA3-AS1 on tumor growth in vivo, and immunohistochemistry was applied to detect expression of ki67 and TUNEL. The results indicate that PSMA3-AS1 was upregulated in FLT3-ITD+ AML patients. Si-PSMA3-AS1 could inhibit the proliferation, autophagy and promote the apoptosis in MV4-11 and Molm13 cells. METTL3 could enhance the PSMA3-AS1 RNA stability. In addition, this study revealed that PSMA3-AS1 affected FLT3-ITD+ AML by targeting expression of miR-20a-5p, and miR-20a-5p further modulated expression of ATG16L1, an mRNA that down-regulated in AML, to affect disease advancement. PSMA3-AS1 could promote FLT3-ITD+ AML progression by regulating the level of autophagy through miR-20a-5p/ATG16L1 pathway. In addition, the increase of PSMA3-AS1 may be caused by the involvement of METTL3 in regulating its stability. This discovery will provide new horizons for early screening and targeted therapy of FLT3-ITD+ AML.

Brainprints: identifying individuals from magnetoencephalograms.

Magnetoencephalography (MEG) is used to study a wide variety of cognitive processes. Increasingly, researchers are adopting principles of open science and releasing their MEG data. While essential for reproducibility, sharing MEG data has unforeseen privacy risks. Individual differences may make a participant identifiable from their anonymized recordings. However, our ability to identify individuals based on these individual differences has not yet been assessed. Here, we propose interpretable MEG features to characterize individual difference. We term these features brainprints (brain fingerprints). We show through several datasets that brainprints accurately identify individuals across days, tasks, and even between MEG and Electroencephalography (EEG). Furthermore, we identify consistent brainprint components that are important for identification. We study the dependence of identifiability on the amount of data available. We also relate identifiability to the level of preprocessing and the experimental task. Our findings reveal specific aspects of individual variability in MEG. They also raise concerns about unregulated sharing of brain data, even if anonymized.