HIV-specific Tregs decrease after IL-2 treatment and positively correlate with viral load after treatment interruption. by Vedran Brezar (337452)

Liquid Crystalline Features in a Polyolefin of Poly(methylene-1,3-cyclopentane) by Naofumi Naga (2084077)

“…A liquid crystalline phase has been discovered in a polyolefin of poly(methylene-1,3-cyclopentane) (PMCP) having low molecular weight, which was obtained with cyclization polymerization of 1,5-hexadiene (HD) using a zirconocene catalyst in the presence of chain transfer reagents. …”

The effect of Gas6/Axl signaling on the expression of ZO-1 and occludin in Caco-2 cells without <i>K</i>. <i>pneumoniae</i> infection. by Hitoshi Tsugawa (296864)

Most important percentage changes in CoA scenarios. by Inmaculada Villanueva-Baxarias (21454246)

Description of results of SD-TOPSIS application (combination A) using selected moment characteristics. by Roman Vavrek (13200141)

Comparison of mitochondrial number at MF and SC presynaptic bouton profiles. by Sang Hun Lee (564624)

Data_Sheet_5_P16INK4a Deletion Ameliorates Damage of Intestinal Epithelial Barrier and Microbial Dysbiosis in a Stress-Induced Premature Senescence Model of Bmi-1 Deficiency.docx by Jiawen Zhou (2323381)

“…P16^INK4a deletion could maintain barrier function and microbiota balance in Bmi-1^–/– mice through strengthening formation of TJ and decreasing macrophages-secreted TNF-α induced by Desulfovibrio entering the intestinal epithelium. …”

Data_Sheet_5_P16INK4a Deletion Ameliorates Damage of Intestinal Epithelial Barrier and Microbial Dysbiosis in a Stress-Induced Premature Senescence Model of Bmi-1 Deficiency.docx by Jiawen Zhou (2323381)

“…P16^INK4a deletion could maintain barrier function and microbiota balance in Bmi-1^–/– mice through strengthening formation of TJ and decreasing macrophages-secreted TNF-α induced by Desulfovibrio entering the intestinal epithelium. …”

Level of mucin secretion and water channel expression. by Ji Eun Kim (403026)

The effect of Gas6 recombinant protein on the expression of ZO-1 and occludin in Caco-2 cells without <i>K</i>. <i>pneumoniae</i> infection. by Hitoshi Tsugawa (296864)

Data cleaning and preparation algorithm. by Ayana Ablayeva (22103708)

“…</p><p>Results</p><p>Over the decade, age-standardized incidence rates decreased from 5.55 to 5.40 per 100,000, while mortality rates rose from 3.75 to 4.75 per 100,000. …”

Nucleotide sequences for hybrid striped bass piscidin gene transcripts. by Scott A. Salger (3072093)

Circulating neutrophil counts increase rapidly during invasive infection, while platelet counts decrease progressively over time. by Sinead M. Hurley (3132807)

Plot showing average position (centroid) of predatory behavior of 18 treatments displayed by snake <i>T</i>. <i>melanogaster</i>, depending of three categories (few, median, many)... by Javier Manjarrez (531011)

Estimates Vaccine effectiveness of inactivated vaccine BBIBP-CorV against COVID-19-associated severe or critical hospitalization according to age and gender over time since second... by Jihane Belayachi (51116)

LY2405319 decreases succinate concentration in liver lysate and serum of MCD diet–induced mouse models of liver fibrosis. by Cong Thuc Le (4853716)

Effect of D₂/D₃ antagonist sulpiride on GBR-induced recognition memory impairments. by Jill Rocchetti (16883936)

Training set data expansion. by Qingjun Yu (1649473)

“…Based on the PyTorch deep learning framework, the initial U²-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”

Structural plane recognition effect. by Qingjun Yu (1649473)

“…Based on the PyTorch deep learning framework, the initial U²-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”

Structural plane classification. by Qingjun Yu (1649473)

“…Based on the PyTorch deep learning framework, the initial U²-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”