Application of Developmental Regulators for Enhancing Plant Regeneration and Genetic Transformation.

Establishing plant regeneration systems and efficient genetic transformation techniques plays a crucial role in plant functional genomics research and the development of new crop varieties. The inefficient methods of transformation and regeneration of recalcitrant species and the genetic dependence of the transformation process remain major obstacles. With the advancement of plant meristematic tissues and somatic embryogenesis research, several key regulatory genes, collectively known as developmental regulators, have been identified. In the field of plant genetic transformation, the application of developmental regulators has recently garnered significant interest. These regulators play important roles in plant growth and development, and when applied in plant genetic transformation, they can effectively enhance the induction and regeneration capabilities of plant meristematic tissues, thus providing important opportunities for improving genetic transformation efficiency. This review focuses on the introduction of several commonly used developmental regulators. By gaining an in-depth understanding of and applying these developmental regulators, it is possible to further enhance the efficiency and success rate of plant genetic transformation, providing strong support for plant breeding and genetic engineering research.

Jidong ovarian aging cohort study: Objective, design, and baseline characteristics.

BACKGROUND: Ovarian aging is a continuous process comprising a gradual decrease in both the quantity and the quality of the oocytes. A decline in ovarian function leads to chronic disease and physiological problems. The aim of this study is to establish a cohort for the purpose of examining the ovarian aging process and its relationship with health status and quality of life in women across all age groups. METHOD: This protocol outlines a community-based, prospective long-term observational study involving 1676 women recruited from Caofeidian District in Tangshan City, Hebei Province, China. Data are gathered by the administration of questionnaires, doing physical examinations, performing blood biochemistry tests, and measuring levels of female hormones. The primary outcomes will be the occurrence of cardiovascular disease, osteoporosis, hypertension, diabetes, hyperlipidemia, and other chronic diseases, assessed according to established diagnostic criteria for each disease. The secondary outcome will be the decline in quality of life during the follow-up period, assessed by the modified Kupperman Index. The study comprises a baseline cross-sectional assessment and a follow-up evaluation. The participants will undergo face-to-face interviews as part of their regular medical examinations until 2026 or until the occurrence of outcome events. DISCUSSION: The results of the prospective study will indicate the association between ovarian aging and the prevalence of chronic diseases as well as diminished quality of life among women across different age categories.

The role of dynamic, static, and delayed total-body PET imaging in the detection and differential diagnosis of oncological lesions.

OBJECTIVES: Commercialized total-body PET scanners can provide high-quality images due to its ultra-high sensitivity. We compared the dynamic, regular static, and delayed 18F-fluorodeoxyglucose (FDG) scans to detect lesions in oncologic patients on a total-body PET/CT scanner. MATERIALS & METHODS: In all, 45 patients were scanned continuously for the first 60 min, followed by a delayed acquisition. FDG metabolic rate was calculated from dynamic data using full compartmental modeling, whereas regular static and delayed SUV images were obtained approximately 60- and 145-min post-injection, respectively. The retention index was computed from static and delayed measures for all lesions. Pearson's correlation and Kruskal-Wallis tests were used to compare parameters. RESULTS: The number of lesions was largely identical between the three protocols, except MRFDG and delayed images on total-body PET only detected 4 and 2 more lesions, respectively (85 total). FDG metabolic rate (MRFDG) image-derived contrast-to-noise ratio and target-to-background ratio were significantly higher than those from static standardized uptake value (SUV) images (P < 0.01), but this is not the case for the delayed images (P > 0.05). Dynamic protocol did not significantly differentiate between benign and malignant lesions just like regular SUV, delayed SUV, and retention index. CONCLUSION: The potential quantitative advantages of dynamic imaging may not improve lesion detection and differential diagnosis significantly on a total-body PET/CT scanner. The same conclusion applied to delayed imaging. This suggested the added benefits of complex imaging protocols must be weighed against the complex implementation in the future. CLINICAL RELEVANCE: Total-body PET/CT was known to significantly improve the PET image quality due to its ultra-high sensitivity. However, whether the dynamic and delay imaging on total-body scanner could show additional clinical benefits is largely unknown. Head-to-head comparison between two protocols is relevant to oncological management.

An [18F]FDG PET/3D-ultrashort echo time MRI-based radiomics model established by machine learning facilitates preoperative assessment of lymph node status in non-small cell lung cancer.

OBJECTIVES: To develop an [18F]FDG PET/3D-UTE model based on clinical factors, three-dimensional ultrashort echo time (3D-UTE), and PET radiomics features via machine learning for the assessment of lymph node (LN) status in non-small cell lung cancer (NSCLC). METHODS: A total of 145 NSCLC patients (training, 101 cases; test, 44 cases) underwent whole-body [18F]FDG PET/CT and chest [18F]FDG PET/MRI were enrolled. Preoperative clinical factors and 3D-UTE, CT, and PET radiomics features were analyzed. The Mann-Whitney U test, LASSO regression, and SelectKBest were used for feature extraction. Five machine learning algorithms were used to establish prediction models, which were evaluated by the area under receiver-operator characteristic (ROC), DeLong test, calibration curves, and decision curve analysis (DCA). RESULTS: A prediction model based on random forest, consisting of four clinical factors, six 3D-UTE, and six PET radiomics features, was used as the final model for PET/3D-UTE. The AUCs of this model were 0.912 and 0.791 in the training and test sets, respectively, which not only showed different degrees of improvement over individual models such as clinical, 3D-UTE, and PET (AUC-training = 0.838, 0.834, and 0.828, AUC-test = 0.756, 0.745, and 0.768, respectively) but also achieved the similar diagnostic efficacy as the optimal PET/CT model (AUC-training = 0.890, AUC-test = 0.793). The calibration curves and DCA indicated good consistency (C-index, 0.912) and clinical utility of this model, respectively. CONCLUSION: The [18F]FDG PET/3D-UTE model based on clinical factors, 3D-UTE, and PET radiomics features using machine learning methods could noninvasively assess the LN status of NSCLC. CLINICAL RELEVANCE STATEMENT: A machine learning model of 18F-fluorodeoxyglucose positron emission tomography/ three-dimensional ultrashort echo time could noninvasively assess the lymph node status of non-small cell lung cancer, which provides a novel method with less radiation burden for clinical practice. KEY POINTS: • The 3D-UTE radiomics model using the PLS-DA classifier was significantly associated with LN status in NSCLC and has similar diagnostic performance as the clinical, CT, and PET models. • The [18F]FDG PET/3D-UTE model based on clinical factors, 3D-UTE, and PET radiomics features using the RF classifier could noninvasively assess the LN status of NSCLC and showed improved diagnostic performance compared to the clinical, 3D-UTE, and PET models. • In the assessment of LN status in NSCLC, the [18F]FDG PET/3D-UTE model has similar diagnostic efficacy as the [18F]FDG PET/CT model that incorporates clinical factors and CT and PET radiomics features.

Facile fabrication and antibacterial properties of chitosan/acrylamide/gold nanocomposite hydrogel incorporated with Chaetomium globosium extracts from Gingko biloba leaves.

Microorganisms are a unique part of our ecosystem because they affect the survival of living organisms. Although pathogenic microorganisms could be detrimental to the plants, animals, and humans, beneficial microbes have provided significant improvement in the growth and development of living organisms. In this study, the fungus Chaetomium globosium was isolated from the medicinal tree Gingko biloba, and then incorporated into a polymerization system to fabricate chitosan/acrylamide/gold (CS/Am/Au) nanocomposite hydrogels. The as-prepared hydrogel displayed increased mechanical strength due to the reinforcement of Au (gold) nanocomposites within the hydrogel matrix. Also, the equilibrium pH responsive swelling rates of the hydrogels gradually increased as the pH increases due to partial acid and basic hydrolysis occurring in the hydrogel as well as formation of hydrogen bond. In addition, the hydrogel demonstrated promising antibacterial activities against selected gram-positive (Staphylococcus epidermidis and Staphylococcus aureus) and gram-negative (Pseudomonas aeruginosa) bacterial strains with an average MIC90 of 0.125 mg/mL at a dosage of 1.0 mg/L. The obtained results are quite promising towards resolving several health challenges and advancing the pharmaceutical industries.

Digenic CHD7 and SMCHD1 inheritance Unveils phenotypic variability in a family mainly presenting with hypogonadotropic hypogonadism.

Objectives: CHARGE syndrome is a congenital hereditary condition involving multiple systems. Patients are easily misdiagnosed with idiopathic hypogonadotropic hypogonadism (IHH) due to the overlap of clinical manifestations. An accurate clinical diagnosis remains challenging when the predominant clinical manifestation resembles hypogonadotropic hypogonadism. Methods: This original research is conducted based on the genetic finding and analysis of clinical cases. Whole-exome sequencing (WES) and in-silico analyse were performed on two sisters to investigate the pathogenesis in this family. Homology modelling was conducted to evaluate structural changes in the variants. Results: WES and Sanger sequencing revealed two siblings carrying a nonsense mutation (NM_017780.4: c.115C > T) in exon 2 of CHD7 inherited from a mildly affected mother and a missense mutation (NM_015295.3: c.2582T > C) in exon 20 of SMCHD1 inherited from an asymptomatic father. The nonsense mutation in CHD7 was predicted to generate nonsense-mediated decay, whereas the missense mutation in SMCHD1 decreased protein stability. Conclusions: We identified digenic CHD7 and SMCHD1 mutations in IHH-associated diseases for the first time and verified the synergistic role of oligogenic inheritance. It was also determined that WES is an effective tool for distinguishing diseases with overlapping features and establishing a molecular diagnosis for cases with digenic or oligogenic hereditary disorders, which is beneficial for timely treatment, and family genetic counseling.

Inferring the Regulatory Network of miRNAs on Terpene Trilactone Biosynthesis Affected by Environmental Conditions.

As a medicinal tree species, ginkgo (Ginkgo biloba L.) and terpene trilactones (TTLs) extracted from its leaves are the main pharmacologic activity constituents and important economic indicators of its value. The accumulation of TTLs is known to be affected by environmental stress, while the regulatory mechanism of environmental response mediated by microRNAs (miRNAs) at the post-transcriptional levels remains unclear. Here, we focused on grafted ginkgo grown in northwestern, southwestern, and eastern-central China and integrally analyzed RNA-seq and small RNA-seq high-throughput sequencing data as well as metabolomics data from leaf samples of ginkgo clones grown in natural environments. The content of bilobalide was highest among detected TTLs, and there was more than a twofold variation in the accumulation of bilobalide between growth conditions. Meanwhile, transcriptome analysis found significant differences in the expression of 19 TTL-related genes among ginkgo leaves from different environments. Small RNA sequencing and analysis showed that 62 of the 521 miRNAs identified were differentially expressed among different samples, especially the expression of miRN50, miR169h/i, and miR169e was susceptible to environmental changes. Further, we found that transcription factors (ERF, MYB, C3H, HD-ZIP, HSF, and NAC) and miRNAs (miR319e/f, miRN2, miRN54, miR157, miR185, and miRN188) could activate or inhibit the expression of TTL-related genes to participate in the regulation of terpene trilactones biosynthesis in ginkgo leaves by weighted gene co-regulatory network analysis. Our findings provide new insights into the understanding of the regulatory mechanism of TTL biosynthesis but also lay the foundation for ginkgo leaves' medicinal value improvement under global change.

Amide Proton Transfer-Weighted Imaging and Multiple Models Intravoxel Incoherent Motion-Based 18 F-FDG PET/MRI for Predicting Progression-Free Survival in Non-Small Cell Lung Cancer.

BACKGROUND: Amide proton transfer-weighted imaging (APTWI) and multiple models intravoxel incoherent motion (IVIM) based 18 F-FDG PET/MR could reflect the microscopic information of the tumor from multiple perspectives. However, its value in the prognostic assessment of non-small cell lung cancer (NSCLC) still needs to be further explored. PURPOSE: To determine whether pretreatment APTWI, mono-, bi-, and stretched-exponential model IVIM, and 18 F-FDG PET-derived parameters of the primary lesion may be associated with progression-free survival (PFS) in NSCLC. STUDY TYPE: Prospective. POPULATION: Seventy-seven patients (mean age, 62 years, range, 20-81 years) with 37 men and 40 women were included. FIELD STRENGTH/SEQUENCE: 3.0 T 18 F-FDG PET/MRI, single shot echo planar imaging sequences for IVIM and fast spin-echo sequences with magnetization transfer pulses for APTWI. ASSESSMENT: Patient clinical characteristics (age, sex, smoke, subtype, TNM stage, and surgery), PFS (chest CT every 3 months, median follow-up was 18 months, range, 4-27 months), and APTWI (MTRasym(3.5 ppm)), IVIM (ADCstand , D, D*, f, DDC, and α), and 18 F-FDG PET (SUVmax , MTV, and TLG) parameters were recorded. STATISTICAL TESTS: Proportional hazards model, concordance index, calibration curve, decision curve analysis (DCA), and Log-rank test. A P value <0.05 was considered statistically significant. RESULTS: Histological subtype, TNM stage, MTV, D*, and MTRasym(3.5 ppm) were all independent predictors of PFS. A prediction model based on these predictors was developed with a C-index of 0.895 (95% CI: 0.839-0.951), which was significantly superior to each of the above predictors alone (C-index = 0.629, 0.707, 0.692, 0.678, and 0.558, respectively). The calibration curve and DCA indicated good consistency and clinical utility of the prediction model, respectively. Log-rank test results showed a significant difference in PFS between the high- and low-risk groups. DATA CONCLUSION: APTWI and multiple models IVIM based 18 F-FDG PET/MRI can be used for PFS assessment in NSCLC. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Injectable Self-Harden Antibiofilm Bioceramic Cement for Minimally Invasive Surgery.

There is an urgent demand for antibacterial bone grafts in clinics. Worryingly, the misuse and overuse of antibiotics accelerate the emergence of drug-resistant bacteria. Therefore, this study prepared a novel injectable bioceramic cement without antibiotics (FS-BCS), which showed good antibacterial properties by loading iron and strontium onto a matrix composed of brushite and calcium sulfate. The setting time, injectability, microstructure, antibacterial properties, anti-biofilm properties, and cytocompatibility of the novel bioceramic cement were evaluated thoroughly. The results showed that the material was highly injectable and antiwashout. The antibacterial tests revealed that FS-BCS inhibited the growth of 99.9% E. coli and S. aureus separately in the broth due to the synergistic effect of strontium and iron. Simultaneously, crystal violet and fluorescent staining tests revealed that the material could significantly inhibit the formation of E. coli and S. aureus biofilms. In addition, the co-incorporation of iron and strontium promoted the proliferation and migration of osteoblasts. Therefore, FS-BCS has good application potential in antibiotic-free anti-infection bone grafting using minimally invasive surgery.

Quantitative parameters of static imaging and fast kinetics imaging in 18F-FDG total-body PET/CT for the assessment of histological feature of pulmonary lesions.

Background: To investigate the value of quantitative parameters related to static imaging and fast kinetics imaging of total-body (TB) 2-[18F]-fluoro-2-deoxy-D-glucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) in differentiating benign from malignant pulmonary lesions and squamous cell carcinoma (SCC) from adenocarcinoma (AC) and to analyze the correlation of each parameter with the Ki-67 index. Methods: A total of 108 patients with pulmonary lesions from July 2021 to May 2022 in the Henan Provincial People's Hospital, China, were consecutively recruited for TB 18F-FDG PET/CT in this prospective study. Static imaging parameters maximum standardized uptake value (SUVmax) and fast kinetics imaging parameters transport constant (K1), rate constants (k2), time delay (td), and fractional blood volume (vb) were calculated and compared. The area under the receiver operating characteristic (ROC) curve (AUC), Delong test, Logistic regression analyses, and Pearson correlation were used to assess diagnostic efficacy, find independent predictors and analyse correlations respectively. Results: Malignant lesions had higher SUVmax and K1 and lower vb than benign lesions, and SCC had higher SUVmax and K1 and lower td and vb than AC (all P<0.05). For the differentiation of benign and malignant lesions, SUVmax, K1, and vb were independent predictors, and AUC (SUVmax + K1+ vb) =0.909 (95% CI: 0.839-0.956), AUC (SUVmax) =0.883 (95% CI: 0.807-0.937), AUC (K1) =0.810 (95% CI: 0.723-0.879), and AUC (vb) =0.746 (95% CI: 0.653-0.825), where AUC (SUVmax + K1+ vb) was significantly different from AUC (K1), AUC (vb) (Z=3.006, 3.965, all P<0.05). For the differentiation of SCC and AC, SUVmax, K1, td, and vb were independent predictors, and AUC (SUVmax + K1+ td + vb) =0.946 (95% CI: 0.840-0.991), AUC (SUVmax) =0.818 (95% CI: 0.680-0.914), AUC (K1) =0.770 (95% CI: 0.626-0.879), AUC (vb) =0.737 (95% CI: 0.590-0.853), and AUC (td) =0.669 (95% CI: 0.510-0.791), where AUC (SUVmax + K1+ td + vb) was significantly different from AUC (SUVmax), AUC (K1), AUC (vb), and AUC (td) (Z=2.269, 2.821, 2.848, and 3.276, all P<0.05). SUVmax and K1 were moderately and mildly positively correlated with the Ki-67 index (r=0.541, 0.452, all P<0.05), respectively. Conclusions: Quantitative parameters of static imaging and fast kinetics imaging in 18F-FDG total-body PET/CT can be used to differentiate benign from malignant pulmonary lesions and SCC from AC and to assess Ki-67 expression.

Nursing assistants' use of best practices and pain in older adults living in nursing homes.

BACKGROUND: Inadequate pain management persists in nursing homes. Nursing assistants provide the most direct care in nursing homes, and significantly improving the quality of care requires their adoption of best care practices informed by the best available evidence. We assessed the association between nursing assistants' use of best practices and residents' pain levels. METHODS: We performed a cross-sectional analysis of data collected between September 2019 and February 2020 from a stratified random sample of 87 urban nursing homes in western Canada. We linked administrative data (the Resident Assessment Instrument-Minimum Data Set [RAI-MDS], 2.0) for 10,093 residents and survey data for 3547 nursing assistants (response rate: 74.2%) at the care unit level. Outcome of interest was residents' pain level, measured by the pain scale derived from RAI-MDS, 2.0. The exposure variable was nursing assistants' use of best practices, measured with validated self-report scales and aggregated to the unit level. Two-level random-intercept multinomial logistic regression accounted for the clustering effect of residents within care units. Covariates included resident demographics and clinical characteristics and characteristics of nursing assistants, unit, and nursing home. RESULTS: Of the residents, 3305 (30.3%) were identified as having pain. On resident care units with higher levels of best practice use among nursing assistants, residents had 32% higher odds of having mild pain (odds ratio, 1.32; 95% confidence interval, 1.01-1.71; p = 0.040), compared with residents on care units with lower levels of best practice use among nursing assistants. The care units did not differ in reported moderate or severe pain among residents. CONCLUSIONS: We observed that higher unit-level best practice use among nursing assistants was associated with mild resident pain. This association warrants further research to identify key individual and organizational factors that promote effective pain assessment and management.

Characterizing worker compensation claims in long-term care and examining the association between facility characteristics and severe injury: a repeated cross-sectional study from Alberta, Canada.

BACKGROUND: Despite the physical demands and risks inherent to working in long-term care (LTC), little is known about workplace injuries and worker compensation claims in this setting. The purpose of this study was to characterize workplace injuries in LTC and to estimate the association between worker and organizational factors on severe injury. METHODS: We used a repeated cross-sectional design to examine worker compensation claims between September 1, 2014 and September 30, 2018 from 25 LTC homes. Worker compensation claim data came from The Workers Compensation Board of Alberta. LTC facility data came from the Translating Research in Elder Care program. We used descriptive statistics to characterize the sample and multivariable logistic regression to estimate the association between staff, organizational, and resident characteristics and severe injury, measured as 31+ days of disability. RESULTS: We examined 3337 compensation claims from 25 LTC facilities. Less than 10% of claims (5.1%, n = 170) resulted in severe injury and most claims did not result in any days of disability (70.9%, n = 2367). Most of the sample were women and over 40 years of age. Care aides were the largest occupational group (62.1%, n = 2072). The highest proportion of claims were made from staff working in voluntary not for profit facilities (41.9%, n = 1398) followed by public not for profit (32.9%, n = 1098), and private for profit (n = 25.2%, n = 841). Most claims identified the nature of injury as traumatic injuries to muscles, tendons, ligaments, or joints. In the multivariable logistic regression, higher staff age (50-59, aOR: 2.26, 95% CI 1.06-4.83; 60+, aOR: 2.70, 95% CI 1.20-6.08) was associated with more severe injury, controlling for resident acuity and other organizational staffing factors. CONCLUSIONS: Most claims were made by care aides and were due to musculoskeletal injuries. In LTC, few worker compensation claims were due to severe injury. More research is needed to delve into the specific features of the LTC setting that are related to worker injury.

Preoperative prediction of lymphovascular invasion of colorectal cancer by radiomics based on 18F-FDG PET-CT and clinical factors.

Purpose: The purpose of this study was to investigate the value of a clinical radiomics model based on Positron emission tomography-computed tomography (PET-CT) radiomics features combined with clinical predictors of Lymphovascular invasion (LVI) in predicting preoperative LVI in patients with colorectal cancer (CRC). Methods: A total of 95 CRC patients who underwent preoperative 18F-fluorodeoxyglucose (FDG) PET-CT examination were retrospectively enrolled. Univariate and multivariate logistic regression analyses were used to analyse clinical factors and PET metabolic data in the LVI-positive and LVI-negative groups to identify independent predictors of LVI. We constructed four prediction models based on radiomics features and clinical data to predict LVI status. The predictive efficacy of different models was evaluated according to the receiver operating characteristic curve. Then, the nomogram of the best model was constructed, and its performance was evaluated using calibration and clinical decision curves. Results: Mean standardized uptake value (SUVmean), maximum tumour diameter and lymph node metastasis were independent predictors of LVI in CRC patients (P < 0.05). The clinical radiomics model obtained the best prediction performance, with an Area Under Curve (AUC) of 0.922 (95%CI 0.820-0.977) and 0.918 (95%CI 0.782-0.982) in the training and validation cohorts, respectively. A nomogram based on the clinical radiomics model was constructed, and the calibration curve fitted well (P > 0.05). Conclusion: The clinical radiomics prediction model constructed in this study has high value in the preoperative individualized prediction of LVI in CRC patients.

Inhibition of checkpoint kinase prevents human oocyte apoptosis induced by chemotherapy and allows enhanced tumour chemotherapeutic efficacy.

STUDY QUESTION: Could inhibition of the checkpoint kinase (CHEK) pathway protect human oocytes and even enhance the anti-tumour effects, during chemotherapy? SUMMARY ANSWER: CHEK inhibitors prevented apoptosis of human oocytes induced by chemotherapy and even enhanced the anti-tumour effects. WHAT IS KNOWN ALREADY: CHEK inhibitors showed ovarian protective effects in mice during chemotherapy, while their role in human oocytes is unclear. STUDY DESIGN, SIZE, DURATION: This experimental study evaluated the ovarian reserve of young patients (120 patients) with cancer, exposed or not exposed to taxane and platinum (TP)-combined chemotherapy. Single RNA-sequencing analysis of human primordial oocytes from 10 patients was performed to explore the mechanism of oocyte apoptosis induced by TP chemotherapy. The damaging effects of paclitaxel (PTX) and cisplatin on human oocytes were also evaluated by culturing human ovaries in vitro. A new mouse model that combines human ovarian xenotransplantation and patient-derived tumour xenografts was developed to explore adjuvant therapies for ovarian protection. The mice were randomly allocated to four groups (10 mice for each group): control, cisplatin, cisplatin + CK1 (CHEK1 inhibitor, SCH 900776), and cisplatin + CK2 (CHEK2 inhibitor, BML277). PARTICIPANTS/MATERIALS, SETTING, METHODS: In the prospective cohort study, human ovarian follicles were counted and serum AMH levels were evaluated. RNA-sequencing analysis was conducted, and staining for follicular damage (phosphorylated H2AX histone; γH2AX), terminal deoxynucleotidyl transferase-mediated dUTP-biotin nick end labelling (TUNEL) assays and assessments of apoptotic biomarkers (western blot and immunofluorescence) were conducted in human ovaries. After the treatments, histological analysis was performed on human ovarian samples to investigate follicular populations, and oocyte damage was measured by γH2AX staining, BAX staining, and TUNEL assays. At the same time, the tumours were evaluated for volume, weight, and apoptosis levels. MAIN RESULTS AND THE ROLE OF CHANCE: Patients who received TP chemotherapy showed decreased ovarian reserves. Single RNA-sequencing analysis of human primordial oocytes indicated that TP chemotherapy induced apoptosis of human primordial oocytes by causing CHEK-mediated TAp63α phosphorylation. In vitro culture of human ovaries showed greater damaging effects on oocytes after cisplatin treatment compared with that after PTX treatment. Using the new animal model, CHEK1/2 inhibitors prevented the apoptosis of human oocytes induced by cisplatin and even enhanced its anti-tumour effects. This protective effect appeared to be mediated by inhibiting DNA damage via the CHEK-TAp63α pathway and by generation of anti-apoptotic signals in the oocytes. LARGE SCALE DATA: N/A. LIMITATIONS, REASONS FOR CAUTION: This was a preclinical study performed with human ovarian samples, and clinical research is required for validation. WIDER IMPLICATIONS OF THE FINDINGS: These findings highlight the therapeutic potential of CHEK1/2 inhibitors as a complementary strategy for preserving fertility in female cancer patients. STUDY FUNDING/COMPETING INTEREST(S): This work was financially supported by the National Natural Science Foundation of China (nos. 82001514 and 81902669) and the Fundamental Research Funds for the Central Universities (2021yjsCXCY087). The authors declare no conflict of interest.

Molecular Characterization and Genetic Diversity of Ginkgo (Ginkgo biloba L.) Based on Insertions and Deletions (InDel) Markers.

As a "living fossil", ginkgo (Ginkgo biloba L.) has significant ornamental, medicinal, and timber value. However, the breeding improvement of ginkgo was limited by the lack of enough excellent germplasms and suitable molecular markers. Here, we characterized numerous polymorphic insertion/deletion (InDel) markers using RAD-seq in 12 different ginkgo cultivars. The total of 279,534 InDels identified were unequally distributed across 12 chromosomes in the ginkgo genome. Of these, 52.56% (146,919) and 47.44% (132,615) were attributed to insertions and deletions, respectively. After random selection and validation, 26 pairs of polymorphic primers were used for molecular diversity analysis in 87 ginkgo cultivars and clones. The average values of observed heterozygosity and polymorphism information were 0.625 and 0.517, respectively. The results of population structure analyses were similar to those of neighbor-joining and principal component analyses, which divided all germplasms into two distinct groups. Moreover, 11 ginkgo core collections accounted for approximately 12.64% of the total ginkgo germplasms obtained, representing well the allelic diversity of all original germplasms. Therefore, these InDels can be used for germplasm management and genetic diversity analyses in ginkgo and the core collections will be used effectively for ginkgo genetic improvement.

The Metasequoia genome and evolutionary relationships among redwoods.

Redwood trees (Sequoioideae), including Metasequoia glyptostroboides (dawn redwood), Sequoiadendron giganteum (giant sequoia), and Sequoia sempervirens (coast redwood), are threatened and widely recognized iconic tree species. Genomic resources for redwood trees could provide clues to their evolutionary relationships. Here, we report the 8-Gb reference genome of M. glyptostroboides and a comparative analysis with two related species. More than 62% of the M. glyptostroboides genome is composed of repetitive sequences. Clade-specific bursts of long terminal repeat retrotransposons may have contributed to genomic differentiation in the three species. The chromosomal synteny between M. glyptostroboides and S. giganteum is extremely high, whereas there has been significant chromosome reorganization in S. sempervirens. Phylogenetic analysis of marker genes indicates that S. sempervirens is an autopolyploid, and more than 48% of the gene trees are incongruent with the species tree. Results of multiple analyses suggest that incomplete lineage sorting (ILS) rather than hybridization explains the inconsistent phylogeny, indicating that genetic variation among redwoods may be due to random retention of polymorphisms in ancestral populations. Functional analysis of ortholog groups indicates that gene families of ion channels, tannin biosynthesis enzymes, and transcription factors for meristem maintenance have expanded in S. giganteum and S. sempervirens, which is consistent with their extreme height. As a wetland-tolerant species, M. glyptostroboides shows a transcriptional response to flooding stress that is conserved with that of analyzed angiosperm species. Our study offers insights into redwood evolution and adaptation and provides genomic resources to aid in their conservation and management.

Ovarian reserve in reproductive-aged patients with cancer before gonadotoxic treatment: a systematic review and meta-analysis.

STUDY QUESTION: Does cancer itself, before any gonadotoxic treatment, affect ovarian function in reproductive-aged patients? SUMMARY ANSWER: Our study revealed that women with cancer may have decreased ovarian reserve markers even before cancer therapy. WHAT IS KNOWN ALREADY: With the field 'oncofertility' improving rapidly, cancer therapy-mediated ovarian damage is well characterized. However, there is a controversy about whether cancer itself affects ovarian function before gonadotoxic treatment. STUDY DESIGN SIZE DURATION: We conducted a systematic meta-analysis investigating the association between cancer and ovarian function prior to gonadotoxic treatment. Titles or abstracts related to ovarian reserve (e.g. anti-Müllerian hormone (AMH), antral follicle count (AFC), or basal follicle-stimulating hormone (FSH)) combined with titles or abstracts related to the exposure (e.g. cancer*, oncolog*, or malignan*) were searched in PubMed, Embase, and Web of Science databases from inception to 1 February 2022. PARTICIPANTS/MATERIALS SETTING METHODS: We included cohort, case-control, and cross-sectional studies in English that examined ovarian reserve in reproductive-aged patients (18-45 years) with cancer compared to age-matched controls before cancer treatment. The quality of the included studies was assessed by ROBINS-I. Fixed or random effects were conducted to estimate standard or weighted mean difference (SMD or WMD, respectively) and CI. Heterogeneity was assessed by the Q test and I2 statistics, and publication bias was evaluated by Egger's and Begg's tests. MAIN RESULTS AND THE ROLE OF CHANCE: The review identified 17 eligible studies for inclusion. The results showed that cancer patients had lower serum AMH levels compared to healthy controls (SMD = -0.19, 95% CI = -0.34 to -0.03, P = 0.001), especially women with hematological malignancies (SMD = -0.62, 95% CI = -0.99 to -0.24, P = 0.001). The AFC was also decreased in patients with cancer (WMD = -0.93, 95% CI = -1.79 to -0.07, P = 0.033) compared to controls, while inhibin B and basal FSH levels showed no statistically significant differences. LIMITATIONS REASONS FOR CAUTION: Serum AMH and basal FSH levels in this meta-analysis showed high heterogeneity, and the small number of studies contributing to most subgroup analyses limited the heterogeneity analysis. Moreover, the studies for specific cancer subtypes may be too small to draw conclusions; more studies are needed to investigate the possible impact of cancer type and stage on ovarian function. WIDER IMPLICATIONS OF THE FINDINGS: Our study confirmed the findings that cancer per se, especially hematological malignancies, negatively affects serum AMH level, and AFC values of reproductive-aged women. However, the lower AMH levels and AFC values may also be due to the changes in ovarian physiology under oncological conditions, rather than actual lower ovarian reserves. Based on the meta-analysis, clinicians should raise awareness about the possible need for personalized approaches for young women with cancer who are interested in pursuing fertility preservation strategies before anticancer treatments. STUDY FUNDING/COMPETING INTERESTS: This work was financially supported by the National Natural Science Foundation of China (nos 81873824, 82001514, and 81902669) and the Applied Basic Research Program of Wuhan Municipal Bureau of Science and Technology (2019020701011436). The authors declare that they have no conflicts of interest. REGISTRATION NUMBER: PROSPERO (CRD42021235954).

Development and validation of the OSASH score to predict overall survival of hepatocellular carcinoma after surgical resection: a dual-institutional study.

OBJECTIVE: To develop and validate a risk score based on preoperative clinical-radiological parameters for predicting overall survival (OS) in patients undergoing surgical resection for hepatocellular carcinoma (HCC). METHODS: From July 2010 to December 2021, consecutive patients with surgically-proven HCC who underwent preoperative contrast-enhanced MRI were retrospectively enrolled. A preoperative OS risk score was constructed in the training cohort using a Cox regression model and validated in a propensity score-matched internal validation cohort and an external validation cohort. RESULTS: A total of 520 patients were enrolled, among whom 210, 210, and 100 patients were from the training, internal validation, and external validation cohorts, respectively. Independent predictors for OS included incomplete tumor "capsule," mosaic architecture, tumor multiplicity, and serum alpha-fetoprotein, which were incorporated into the "OSASH score." The C-index the OSASH score was 0.85, 0.81, and 0.62 in the training, internal, and external validation cohorts, respectively. Using 32 as the cutoff point, the OSASH score stratified patients into prognostically distinct low- and high-risk groups among all study cohorts and six subgroups (all p < 0.05). Furthermore, patients with BCLC stage B-C HCC and OSASH-low risk achieved comparable OS to that of patients with BCLC stage 0-A HCC and OSASH-high risk in the internal validation cohort (5-year OS rates, 74.7 vs. 77.8%; p = 0.964). CONCLUSION: The OSASH score may help predict OS in HCC patients undergoing hepatectomy and identify potential surgical candidates among those with BCLC stage B-C HCC. CLINICAL RELEVANCE STATEMENT: By incorporating three preoperative MRI features and serum AFP, the OSASH score may help predict postsurgical overall survival in patients with hepatocellular carcinoma and identify potential surgical candidates among those with BCLC stage B and C HCC. KEY POINTS: • The OSASH score incorporating three MRI features and serum AFP can be used to predict OS in HCC patients who received curative-intent hepatectomy. • The score stratified patients into prognostically distinct low- and high-risk strata in all study cohorts and six subgroups. • Among patients with BCLC stage B and C HCC, the score identified a subgroup of low-risk patients who achieved favorable outcomes after surgery.

Assessment and quantification of ovarian reserve on the basis of machine learning models.

Background: Early detection of ovarian aging is of huge importance, although no ideal marker or acknowledged evaluation system exists. The purpose of this study was to develop a better prediction model to assess and quantify ovarian reserve using machine learning methods. Methods: This is a multicenter, nationwide population-based study including a total of 1,020 healthy women. For these healthy women, their ovarian reserve was quantified in the form of ovarian age, which was assumed equal to their chronological age, and least absolute shrinkage and selection operator (LASSO) regression was used to select features to construct models. Seven machine learning methods, namely artificial neural network (ANN), support vector machine (SVM), generalized linear model (GLM), K-nearest neighbors regression (KNN), gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM) were applied to construct prediction models separately. Pearson's correlation coefficient (PCC), mean absolute error (MAE), and mean squared error (MSE) were used to compare the efficiency and stability of these models. Results: Anti-Müllerian hormone (AMH) and antral follicle count (AFC) were detected to have the highest absolute PCC values of 0.45 and 0.43 with age and held similar age distribution curves. The LightGBM model was thought to be the most suitable model for ovarian age after ranking analysis, combining PCC, MAE, and MSE values. The LightGBM model obtained PCC values of 0.82, 0.56, and 0.70 for the training set, the test set, and the entire dataset, respectively. The LightGBM method still held the lowest MAE and cross-validated MSE values. Further, in two different age groups (20-35 and >35 years), the LightGBM model also obtained the lowest MAE value of 2.88 for women between the ages of 20 and 35 years and the second lowest MAE value of 5.12 for women over the age of 35 years. Conclusion: Machine learning methods combining multi-features were reliable in assessing and quantifying ovarian reserve, and the LightGBM method turned out to be the approach with the best result, especially in the child-bearing age group of 20 to 35 years.

Fibroadipose vascular anomaly: a clinicopathological study of 75 cases.

AIMS: Fibroadipose vascular anomaly (FAVA) is a complex vascular malformation that is likely to be under-recognised. In this study we aimed to report the pathological features and somatic PIK3CA mutations associated with the most common clinicopathological features. METHODS AND RESULTS: Cases were identified by reviewing the lesions resected from patients with FAVA registered at our Haemangioma Surgery Centre and unusual intramuscular vascular anomalies in our pathology database. There were 23 males and 52 females, who ranged in age from 1 to 51 years. Most cases occurred in the lower extremities (n = 62). The majority of the lesions were intramuscular, with a few disrupting the overlying fascia and involving subcutaneous fat (19 of 75), and a minority of the cases had cutaneous vascular stains (13 of 75). Histopathologically, the lesion was composed of anomalous vascular components that were intertwined with mature adipocytic and dense fibrous tissues and vascular components with: (a) clusters of thin-walled channels, some with blood-filled nodules and others with thin walls resembling pulmonary alveoli; (b) numerous small vessels (arteries, veins and indeterminate channels) - proliferative small blood vessels were often mixed with adipose tissue; (c) larger abnormal venous channels usually irregularly and sometimes excessively muscularised; (d) lymphoid aggregates or lymphoplasmacytic aggregates were usually observed; and (e) lymphatic malformations were sometimes seen as minor elements. All patients had their lessons subjected to PCR, and 53 patients had somatic PIK3CA mutations (53 of 75). CONCLUSIONS: FAVA is a slow-flow vascular malformation with specific clinicopathological and molecular characteristics. Its recognition is fundamental for its clinical/prognostic implications and for targeted therapy.