Journal: Frontiers in Immunology

Article Title: Epigenetic therapy reprograms M2-type tumor-associated macrophages into an M1-like phenotype by upregulating miR-7083-5p

doi: 10.3389/fimmu.2022.976196

Figure Lengend Snippet: Conditioned medium (CM) of M2-type macrophages treated with the combination of 5-aza-dC and TSA inhibits tumor cell survival and sensitizes tumor cells to chemotherapy. (A) Cell viability of 4T1 tumor cells after treatment with 50 nM 5-aza-dC (referred as A) and 25 nM TSA(referred as T), alone or in combination (A+T), for 24–72 (h) (B) Cell viability of 4T1 tumor cells after incubation with the CM of M2-macrophages (M2) treated with 5-aza-dC (M2A) and TSA (M2T), alone or in combination (M2AT), in the absence (blue bars) or presence of 1 μM paclitaxel (PTX, red bars), for 24 h. Black bars represent untreated (-) and PTX-treated tumor cells in the absence of CM. The CM of M1-macrophages (M1) was used as a control. Data represent the mean ± SD of three separate experiments performed in triplicates. *, P <0.05; ***, P <0.001; n.s., not significant, as assessed using one-way ANOVA followed by Tukey’s multiple comparison post-hoc test (A) or two-way ANOVA followed by Bonferroni multiple comparisons post-hoc test (B) .

Article Snippet: To examine the effect of the conditioned medium (CM) of cultured macrophages, tumor cells were incubated with the CM of M2 macrophages in the absence or presence of 1 μM of paclitaxel for 24 h. After treatment, the cells were incubated with a fresh culture medium containing 10% Cell Counting Kit-8 solution (Dojindo, Kumamoto, Japan) for 1–4 h. Absorbance was measured at the wavelength of 450 nm and cell viability was calculated based on the absorbance.

Techniques: Incubation, Control, Comparison

Journal: NPJ Digital Medicine

Article Title: Machine learning for accurate estimation of fetal gestational age based on ultrasound images

doi: 10.1038/s41746-023-00774-2

Figure Lengend Snippet: Demographics of women included in this study.

Article Snippet: Women enroled in INTERBIO-21st had a higher mean weight and body mass index than those participating in INTERGROWTH-21st and also a higher rate of preterm birth (11.8% versus 4.7 and 2.8% in the training and internal validation datasets from INTERGROWTH-21st), which is expected given the higher risk status.

Techniques: Biomarker Discovery

Journal: NPJ Digital Medicine

Article Title: Machine learning for accurate estimation of fetal gestational age based on ultrasound images

doi: 10.1038/s41746-023-00774-2

Figure Lengend Snippet: a Performance per plane in the INTERGROWTH-21st internal validation set.

Article Snippet: Women enroled in INTERBIO-21st had a higher mean weight and body mass index than those participating in INTERGROWTH-21st and also a higher rate of preterm birth (11.8% versus 4.7 and 2.8% in the training and internal validation datasets from INTERGROWTH-21st), which is expected given the higher risk status.

Techniques: Biomarker Discovery

Journal: NPJ Digital Medicine

Article Title: Machine learning for accurate estimation of fetal gestational age based on ultrasound images

doi: 10.1038/s41746-023-00774-2

Figure Lengend Snippet: Table showing comparison of MultiPlane performance to biometry-based methods of gestational age estimation throughout gestation.

Article Snippet: Women enroled in INTERBIO-21st had a higher mean weight and body mass index than those participating in INTERGROWTH-21st and also a higher rate of preterm birth (11.8% versus 4.7 and 2.8% in the training and internal validation datasets from INTERGROWTH-21st), which is expected given the higher risk status.

Techniques: Comparison, Biomarker Discovery

Journal: NPJ Digital Medicine

Article Title: Machine learning for accurate estimation of fetal gestational age based on ultrasound images

doi: 10.1038/s41746-023-00774-2

Figure Lengend Snippet: Modified Bland-Altman plots of the performance of the gestational age (GA) estimation models on the INTERGROWTH-21st dataset. The striations visible on the data points for the single standard plane models are due to the CORAL binning process employed during training, which is removed for the final MultiPlane regression loss. Due to the variation in the number of data points per figure, the transparency of each scatter point was normalised so that the overall appearance is normalised. HCP Head Circumference Plane; GA Gestational Age; CORAL Consistent Ordinal RAnk Logits; GT Ground Truth; SD Standard Deviation; ACP Abdominal Circumference Plane; FLP Femur Length Plane.

Article Snippet: Women enroled in INTERBIO-21st had a higher mean weight and body mass index than those participating in INTERGROWTH-21st and also a higher rate of preterm birth (11.8% versus 4.7 and 2.8% in the training and internal validation datasets from INTERGROWTH-21st), which is expected given the higher risk status.

Techniques: Modification, Standard Deviation

Journal: NPJ Digital Medicine

Article Title: Machine learning for accurate estimation of fetal gestational age based on ultrasound images

doi: 10.1038/s41746-023-00774-2

Figure Lengend Snippet: Gestational age (GA) estimation results in pregnancies resulting in small for gestational age (SGA) or large for gestational age (LGA) newborns, defined by a birth weight >90th centile (LGA) or <10th centile (SGA) according to the INTERGROWTH-21st international standard .

Article Snippet: Women enroled in INTERBIO-21st had a higher mean weight and body mass index than those participating in INTERGROWTH-21st and also a higher rate of preterm birth (11.8% versus 4.7 and 2.8% in the training and internal validation datasets from INTERGROWTH-21st), which is expected given the higher risk status.

Techniques: