With the rapid development of computer vision technology, deep learning models have demonstrated new research area and potential value in intelligent microbiological detection. By utilizing multilayer neural networks and large amounts of training data, these models are capable of automated extraction and analysis for complex features, thereby improving the efficiency and accuracy of detection. This paper introduces the research background of deep learning in microbiological image detection, and elaborates on the methods for constructing microbiological image datasets, including data collection, preprocessing, annotation, and partitioning, and introduces typical deep learning models as well as their application examples in various microbiological detection. Deep learning in microbiological image analysis faces numerous challenges which needs further development.

Objective With the gradual advancement of China's lunar exploration program and the construction plan for lunar bases,the technology of docking and assembling mobile lunar modules has become an important means for long-term habitation of lunar mobile modules and the construction of lunar bases in the future.Therefore,the design of flexible docking structures between lunar modules has become an urgent problem to be solved.Methods To address the issue of precise docking of mobile lunar modules on the lunar surface,which is severely affected by the uneven terrain and settlement,this paper proposes a flexible docking segment structure composed of a skin and a skeleton.Results The structure deforms to meet the large tolerance docking range required between lunar mobile modules.In terms of skin design,the docking segment structure uses a variety of composite materials to form a flexible skin to cope with the lunar surface environment problems such as radiation,wide temperature variations,and high-speed meteoroid impacts.In terms of skeleton design,a corrugated skeleton structure scheme is presented.Conclusion Based on Ansys and Adams software,static and dynamic simulation analyses of the skeleton structure were conducted,verifying the feasibility of this structure as a flexible docking structure between lunar modules.

With the rapid development of computer vision technology, deep learning models have demonstrated new research area and potential value in intelligent microbiological detection. By utilizing multilayer neural networks and large amounts of training data, these models are capable of automated extraction and analysis for complex features, thereby improving the efficiency and accuracy of detection. This paper introduces the research background of deep learning in microbiological image detection, and elaborates on the methods for constructing microbiological image datasets, including data collection, preprocessing, annotation, and partitioning, and introduces typical deep learning models as well as their application examples in various microbiological detection. Deep learning in microbiological image analysis faces numerous challenges which needs further development.

Objective:To explore the early predictive value of umbilical cord blood S100β protein and lactate combined with amplitude integrated electroencephalogram（aEEG）in small for gestational age（SGA）preterm infants with brain injury.Methods:One hundred and six cases of SGA preterm infants were enrolled in this study in Neonatology Department of Inner Mongolia People's Hospital from January 2019 to December 2021. Umbilical cord blood serum S100β protein and lactate at birth of All SGA preterm infants were tested，and aEEG was monitored at 6h and 72 h after birth，corrected gestational age of 32 weeks and 37 weeks. According to the diagnostic criteria of brain injury in preterm infants，SGA preterm infants were divided into brain injury group（45 cases）and non-brain injury group（61 cases），and compared the differences of S100β protein，lactate and the designated time aEEG between the two groups.SGA preterm infants with brain injury were further divided into symmetrical group（28 cases）and non-symmetrical group（15 cases）. The differences of umbilical cord blood S100β protein and lactate level between the two groups were compared，and the diagnostic value in different types of SGA preterm infants with brain injury was also compared.Results:SGA preterm infants in the brain injury group had significantly higher levels of umbilical cord blood S100β protein［（0.826±0.218）μg/L vs（0.397±0.196）μg/L， t=8.316， P<0.05］and lactate［（8.5±1.3）mmol/L vs（3.8±0.9）mmol/L， t=3.281， P<0.05］than those in non-brain injury group.Symmetric SGA group had higher level of S100β protein than the asymmetric SGA group［（0.924±0.205）μg/L vs（0.438±0.196）μg/L， t=5.734， P<0.05］.But there was no statistically significant difference in lactate levels［（5.6±1.4）mmol/L vs（3.9±1.2）mmol/L， t=0.932， P>0.05］between symmetric SGA group and asymmetric SGA group. The abnormal rates of aEEG in brain injury group and non-brain injury group were respectively 100%（45/45）vs 22.95%（14/61）at 6 h after birth，95.56%（43/45）vs 16.39%（10/61）at 72 h after birth，62.22%（28/45）vs 6.56%（4/61）at 32 weeks of corrected gestational age，22.22%（10/45）vs 3.28%（2/61）at 37 weeks of corrected gestational age. The abnormal rate of brain injury group was higher than the non-brain injury group in the same nodal time，and the differences were statistically significant（ χ 2 value respectively 62.292，64.913，38.074，9.257，all P<0.05）. Conclusion:There were significant value in umbilical cord blood S100β protein，lactate level and aEEG monitoring in the early diagnosis in preterm infants SGA with brain injury. The combination of the three might be more helpful for the early diagnosis and timely treatment of brain injury in SGA preterm infants.

Rectal cancer is one of the most common gastrointestinal malignancies in China. Accurate and reasonable assessment of the preoperative staging of rectal cancer can significantly enhance treatment outcomes and improve patient prognosis. Magnetic resonance imaging is the technique of choice for local staging of rectal cancer and has significant advantages in the diagnosis of rectal primary tumors (T) and peri-intestinal lymph nodes (N). In this review paper, the research ideas and progress of traditional radiomics and deep learning methods for preoperative TN staging prediction of rectal cancer were reviewed around multimodal magnetic resonance images, with the aim of providing new ideas for realizing fully automated TN staging algorithms for rectal cancer.

Objective:To study the role of a novel brain-derived peptide hypoxic-ischemic brain damage associated peptide (HIBDAP) in regulating pyroptosis of oxygen-glucose deprived (OGD) microglia.Methods:The sequence of HIBDAP was coupled with the sequence of cell-penetrating peptide transactivator of transcription (TAT) to form TAT-HIBDAP. Fluorescein isothiocyanate (FITC) labeled TAT-HIBDAP was added to microglia cells and observed under fluorescence microscope. Microglia cells were treated with different concentrations of TAT-HIBDAP (1, 5, 10, 20 μmol/L) and then OGD process. Cell pyroptosis was analyzed using lactate dehydrogenase (LDH) assay. The concentration of TAT-HIBDAP with the most prominent inhibiting effects was determined and selected for subsequent experiments. The pyroptosis morphology of the control group, the OGD group and the HIBDAP group (5 μmol/L TAT-HIBDAP+OGD) was observed using transmission electron microscope. The mRNA and protein expression of NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasomes were examined using real-time quantitative PCR and Western Blot analysis.Results:Fluorescence microscope showed FITC-labeled TAT-HIBDAP could successfully enter microglia cells. Compared with the OGD group, low concentrations of TAT-HIBDAP (1, 5, 10 μmol/L) could significantly reduce microglia pyroptosis and the concentration of 5 μmol/L showed the most prominent effects. Compared with the control group, OGD group showed typical pyroptosis morphology and HIBDAP group showed significantly improved morphology. The mRNA and protein expression of NLRP3 inflammasomes in the OGD group were significantly higher than the control group and also the HIBDAP group.Conclusions:The novel brain-derived peptide HIBDAP may reduce the expression of NLRP3 inflammasomes and inhibit the pyroptosis of OGD microglia.

Gluconacetobacter xylinus is a primary strain producing bacterial cellulose (BC). In G. xylinus, BcsD is a subunit of cellulose synthase and is participated in the assembly process of BC. A series of G. xylinus with different expression levels of the bcsD gene were obtained by using the CRISPR/dCas9 technique. Analysis of the structural characteristics of BC showed that the crystallinity and porosity of BC changed with the expression of bcsD. The porosity varied from 59.95%-84.05%, and the crystallinity varied from 74.26%-93.75%, while the yield of BC did not decrease significantly upon changing the expression levels of bcsD. The results showed that the porosity of bacterial cellulose significantly increased, while the crystallinity was positively correlated with the expression of bcsD, when the expression level of bcsD was below 55.34%. By altering the expression level of the bcsD gene, obtaining BC with different structures but stable yield through a one-step fermentation of G. xylinus was achieved.
Cellulose/chemistry* ; Clustered Regularly Interspaced Short Palindromic Repeats ; Fermentation ; Gluconacetobacter xylinus/metabolism*

Objective:To investigate the effects of standardized treatment combined with medical nutrition intervention on blood glucose level, body mass management and glucose metabolism at 3 months postpartum in patients with gestational diabetes mellitus (GDM).Methods:A total of 114 patients with GDM who received treatment in Shunyi District Hospital of Beijing from June 2017 to October 2019 were included in this study. They were randomly divided into observation group ( n = 57) and control group ( n = 57). The control group was treated with standardized therapy, and the observation group was treated with standardized therapy combined with medical nutrition intervention. Blood glucose level, body mass management, glucose metabolism outcomes at 3 months postpartum, pregnancy outcome, and neonatal outcome were compared between the two groups. Results:After treatment, hemoglobin A1c (HbA1c), fasting blood glucose, 2-hour plasma glucose (2hPG) after breakfast, and 2hPG after dinner in the observation group were (5.20 ± 0.34)%, (4.69 ± 0.31) mmol/L, (7.32 ± 2.13) mmol/L, and (7.54 ± 2.36) mmol/L, respectively, which were significantly lower than those in the control group [(6.38 ± 0.42)%, (6.34 ± 0.45) mmol/L, (9.01 ± 2.27) mmol/L, (9.35 ± 2.47) mmol/L, t = 16.48, 22.79, 4.09, 4.00, all P < 0.001]. The increases in body mass and body mass index during pregnancy in the observation groups were (12.19 ± 2.35) kg and (4.52 ± 1.13) kg/m 2, respectively, which were significantly lower than those in the control group [(16.21 ± 2.64) kg, (6.11 ± 1.25) kg/m 2, t = 8.58, 7.12, both P < 0.001]. The abnormal rate of glucose metabolism at 3 months postpartum in the observation group was significantly lower than that in the control group [5.3% (3/57) vs. 8.8% (5/57), χ2 = 0.53, P = 0.462]. The incidences of premature rupture of membranes, polyhydramnios, and cesarean section in the observation group were 5.3% (3/57), 14.0% (8/57) and 15.8% (9/57), which were significantly lower than those in the control group [22.8% (13/57), 35.1% (20/57), 40.4% (23/57), χ2 = 7.27, 6.81, 8.51, all P < 0.05]. There were no significant differences in the incidences of pregnancy-induced hypertension and postpartum hemorrhage between the two groups (both P > 0.05). The incidences of premature births, macrosomia, respiratory distress, neonatal hypoglycemia and hyperbilirubinemia in the observation groups were 5.3% (3/57), 3.5% (2/57), 7.0% (4/57), 3.5% (2/57), 5.3% (3/57), respectively, which were significantly lower than those in the control group [22.8% (13/57), 17.5% (10/57), 21.1% (12/57), 15.8% (9/57), 19.3% (11/57), χ2 = 7.27, 5.96, 5.60, 4.93, 5.21, all P < 0.05). Conclusion:Standardized treatment combined with medical nutrition intervention can effectively reduce blood glucose level in patients with GMD, control body mass, and improve glucose metabolism at 3 months after delivery.