[Analysis of respiratory syncytial virus nonstructural protein 1 amino acid variation and clinical characteristics]

Objective: To investigate the relationship between amino acid variations of respiratory syncytial virus (RSV) nonstructural protein (NS) 1 and the clinical characteristics. Method: A retrospective case review was conducted. From December 2018 to January 2020, a total of 81 cases of hospitalized children who were tested only positive for RSV by RT-PCR or PCR at the Department of Respiratory Medicine, Children's Hospital of Chongqing Medical University were included in the study. The NS1 genes of RSV subtype A and subtype B were amplified by PCR and sequenced. The amino acid sequences were analyzed. The Chi-square test and Mann-Whitney rank sum test were used to compare the clinical characteristics and type Ⅰ interferon levels of children with or without NS1 variation in the variation and non-variation groups. Results: Among 81 cases, there were 58 males and 23 females. There were 11 cases in the variation group, the age of onset was 2.0 (1.0, 11.0) months, included 4 cases of subtype A (variant sites were: 2 cases for Lys33Gln, one case for Gly2Asp, Pro67Ser, Leu137Phe, respectively) and 7 cases of subtype B (variant sites were: two cases for Val121Ile, one case for Tyr30Cys, Val65Met, Asn85Ser, Ser118Asn, Asp124Asn, respectively). These variant sites all appeared at a very low frequency 0.08 (0.04, 0.29) % in the NCBI PROTEIN database. There were 70 cases in non-variation group, the onset age was 3.5 (1.0, 7.0) months. The proportion of dyspnea in the variation group was higher than that in the non-variation group (10/11 vs. 47% (33/70), χ²=7.31, P<0.01). Conclusions: There are some variant sites in nonstructural protein NS1 of RSV. Children may be prone to have dyspnea with NS1 variations.

A pretreatment scheme for plasmid extraction contained sugar, high concentration lysozyme and mild lysozyme removal

To address the issue of low efficiency in extracting plasmid DNA (pDNA) from Lactobacillus plantarum by breaking the cell wall, we proposed an effective pretreatment scheme. This study investigated the impacts of lysozyme concentrations and glucose, as well as centrifugal forces during lysozyme removal in the pretreatment system. The efficiency of pDNA extraction was assessed using non-staining method, acridine orange staining method (AO staining) and agarose gel electrophoresis (AGE). Furthermore, the glucose high lysozyme method was compared to the commercial kit method and the lysozyme removal method using L. plantarum PC518, 9L15, JS193 and Staphylococcus aureus USA300. The results indicated that the pDNA extraction concentrations from the four tested strains were increased by 8.9, 7.2, 8.5 and 3.6 times, respectively, compared to the commercial kit method. Furthermore, they increased by 1.9, 1.5, 1.8, and 1.4 times, respectively, compared to the lysozyme removal method. The maximum average concentration of pDNA extraction (from L. plantarum PC518) reached 590.8 ± 31.9 ng/ul. In conclusion, the incorporation of sugar, high concentration lysozyme and mild lysozyme removal proved to be effective enhancements in improving the efficiency of pDNA extraction from L. plantarum. Using the pretreatment scheme, the concentration of pDNA extraction was significantly increased, approaching levels comparable to pDNA extraction from Gram-negative bacteria.

Single-cell sequencing analysis of peripheral blood in patients with moyamoya disease

BACKGROUND

At present, the etiology of moyamoya disease is not clear, and it is necessary to explore the mechanism of its occurrence and development. Although some bulk sequencing data have previously revealed transcriptomic changes in Moyamoya disease, single-cell sequencing data has been lacking.

METHODS

Two DSA(Digital Subtraction Angiography)-diagnosed patients with moyamoya disease were recruited between January 2021 and December 2021. Their peripheral blood samples were single-cell sequenced. CellRanger(10 x Genomics, version 3.0.1) was used to process the raw data, demultiplex cellular barcodes, map reads to the transcriptome, and dowm-sample reads(as required to generate normalized aggregate data across samples). There were 4 normal control samples, including two normal samples GSM5160432 and GSM5160434 of GSE168732, and two normal samples of GSE155698, namely GSM4710726 and GSM4710727. Weighted co-expression network analysis was used to explore the gene sets associated with moyamoya disease. GO analysis and KEGG analysis were used to explore gene enrichment pathways. Pseudo-time series analysis and cell interaction analysis were used to explore cell differentiation and cell interaction.

RESULTS

For the first time, we present a peripheral blood single cell sequencing landscape of Moyamoya disease, revealing cellular heterogeneity and gene expression heterogeneity. In addition, by combining with WGCNA analysis in public database and taking intersection, the key genes in moyamoya disease were obtained. namely PTP4A1, SPINT2, CSTB, PLA2G16, GPX1, HN1, LGALS3BP, IFI6, NDRG1, GOLGA2, LGALS3. Moreover, pseudo-time series analysis and cell interaction analysis revealed the differentiation of immune cells and the relationship between immune cells in Moyamoya disease.

CONCLUSIONS

Our study can provide information for the diagnosis and treatment of moyamoya disease.

Application of lung ultrasound in monitoring bronchopulmonary dysplasia and pulmonary arterial pressure in preterm infants

OBJECTIVE

The aim of this study was to evaluate the application value of lung ultrasound in monitoring bronchopulmonary dysplasia (BPD) and pulmonary artery pressure in premature infants.

PATIENTS AND METHODS

A total of 98 preterm infants diagnosed with BPD in the Fourth Hospital in Shijiazhuang were recruited, and their disease severity was classified as mild (n=32), moderate (n=33), or severe BPD (n=33) based on gestational age and oxygen concentration. Lung ultrasonography of the children was performed. The correlation between lung ventilation scores and disease severity was statistically analyzed, and the discrete optimization results were documented. The pulmonary hypertension indexes of the three groups of children were compared.

RESULTS

Aberrant alterations of the pleural line were observed in all included children, and the B-line rose as the disease progressed. The duration of invasive ventilation, medication, and hospital stay increased with disease exacerbation (p<0.05). The three groups significantly differed in terms of ultrasound pulmonary ventilation scores and clinical severity (p<0.05). Only mild BDP was identified by lung ultrasound on the first day of birth (T1), and severe BDP was detectable during the first and second week (T2-T3) as well as the third and fourth week (T4-T5). Severe BPD was associated with significantly higher levels of pulmonary hypertension indices vs. mild and moderate BPD (p<0.05).

CONCLUSIONS

Pulmonary ultrasonography demonstrates great potential to predict pulmonary hypertension in children and assesses the disease severity. Pulmonary ultrasound allows for dynamical real-time observation of the pulmonary lesions in children with pulmonary hypertension, thereby revealing the severity of pulmonary hypertension in premature children.

Significance of liquid-liquid phase separation (LLPS)-related genes in breast cancer: a multi-omics analysis

Currently, the role of liquid-liquid phase separation (LLPS) in cancer has been preliminarily explained. However, the significance of LLPS in breast cancer is unclear. In this study, single cell sequencing datasets GSE188600 and GSE198745 for breast cancer were downloaded from the GEO database. Transcriptome sequencing data for breast cancer were downloaded from UCSC database. We divided breast cancer cells into high-LLPS group and low-LLPS group by down dimension clustering analysis of single-cell sequencing data set, and obtained differentially expressed genes between the two groups. Subsequently, weighted co-expression network analysis (WGCNA) was performed on transcriptome sequencing data, and the module genes most associated with LLPS were obtained. COX regression and Lasso regression were performed and the prognostic model was constructed. Subsequently, survival analysis, principal component analysis, clinical correlation analysis, and nomogram construction were used to evaluate the significance of the prognostic model. Finally, cell experiments were used to verify the function of the model's key gene, PGAM1. We constructed a LLPS-related prognosis model consisting of nine genes: POLR3GL, PLAT, NDRG1, HMGB3, HSPH1, PSMD7, PDCD2, NONO and PGAM1. By calculating LLPS-related risk scores, breast cancer patients could be divided into high-risk and low-risk groups, with the high-risk group having a significantly worse prognosis. Cell experiments showed that the activity, proliferation, invasion and healing ability of breast cancer cell lines were significantly decreased after knockdown of the key gene PGAM1 in the model. Our study provides a new idea for prognostic stratification of breast cancer and provides a novel marker: PGAM1.

Effects of warming on seed germination of woody species in temperate secondary forests

Seed germination, a critical stage of the plant life cycle providing a link between seeds and seedlings, is commonly temperature-dependent. The global average surface temperature is expected to rise, but little is known about the responses of seed germination of woody plants in temperate forests to warming. In the present study, dried seeds of 23 common woody species in temperate secondary forests were incubated at three temperature sequences without cold stratification and after experiencing cold stratification. We calculated five seed germination indices and the comprehensive membership function value that summarized the above indicators. Compared to the control, +2 and +4 °C treatments without cold stratification shortened germination time by 14% and 16% and increased the germination index by 17% and 26%, respectively. For stratified seeds, +4 °C treatment increased germination percentage by 49%, and +4 and +2 °C treatments increased duration of germination and the germination index, and shortened mean germination time by 69%, 458%, 29% and 68%, 110%, 12%, respectively. The germination of Fraxinus rhynchophylla and Larix kaempferi were most sensitive to warming without and with cold stratification, respectively. Seed germination of shrubs was the least sensitive to warming among functional types. These findings indicate warming (especially extreme warming) will enhance the seedling recruitment of temperate woody species, primarily via shortening the germination time, particularly for seeds that have undergone cold stratification. In addition, shrubs might narrow their distribution range.

Identification of high-risk factors associated with mortality at 1-, 3-, and 5-year intervals in gastric cancer patients undergoing radical surgery and immunotherapy: an 8-year multicenter retrospective analysis

Background

Combining immunotherapy with surgical intervention is a prevailing and radical therapeutic strategy for individuals afflicted with gastric carcinoma; nonetheless, certain patients exhibit unfavorable prognoses even subsequent to this treatment regimen. This research endeavors to devise a machine learning algorithm to recognize risk factors with a high probability of inducing mortality among patients diagnosed with gastric cancer, both prior to and during their course of treatment.

Methods

Within the purview of this investigation, a cohort of 1015 individuals with gastric cancer were incorporated, and 39 variables encompassing diverse features were recorded. To construct the models, we employed three distinct machine learning algorithms, specifically extreme gradient boosting (XGBoost), random forest (RF), and k-nearest neighbor algorithm (KNN). The models were subjected to internal validation through employment of the k-fold cross-validation technique, and subsequently, an external dataset was utilized to externally validate the models.

Results

In comparison to other machine learning algorithms employed, the XGBoost algorithm demonstrated superior predictive capacity regarding the risk factors that affect mortality after combination therapy in gastric cancer patients for a duration of one year, three years, and five years posttreatment. The common risk factors that significantly impacted patient survival during the aforementioned time intervals were identified as advanced age, tumor invasion, tumor lymph node metastasis, tumor peripheral nerve invasion (PNI), multiple tumors, tumor size, carcinoembryonic antigen (CEA) level, carbohydrate antigen 125 (CA125) level, carbohydrate antigen 72-4 (CA72-4) level, and H. pylori infection.

Conclusion

The XGBoost algorithm can assist clinicians in identifying pivotal prognostic factors that are of clinical significance and can contribute toward individualized patient monitoring and management.

A novel T-cell exhaustion-related feature can accurately predict the prognosis of OC patients

The phenomenon of T Cell exhaustion (TEX) entails a progressive deterioration in the functionality of T cells within the immune system during prolonged conflicts with chronic infections or tumors. In the context of ovarian cancer immunotherapy, the development, and outcome of treatment are closely linked to T-cell exhaustion. Hence, gaining an in-depth understanding of the features of TEX within the immune microenvironment of ovarian cancer is of paramount importance for the management of OC patients. To this end, we leveraged single-cell RNA data from OC to perform clustering and identify T-cell marker genes utilizing the Unified Modal Approximation and Projection (UMAP) approach. Through GSVA and WGCNA in bulk RNA-seq data, we identified 185 TEX-related genes (TEXRGs). Subsequently, we transformed ten machine learning algorithms into 80 combinations and selected the most optimal one to construct TEX-related prognostic features (TEXRPS) based on the mean C-index of the three OC cohorts. In addition, we explored the disparities in clinicopathological features, mutational status, immune cell infiltration, and immunotherapy efficacy between the high-risk (HR) and low-risk (LR) groups. Upon the integration of clinicopathological features, TEXRPS displayed robust predictive power. Notably, patients in the LR group exhibited a superior prognosis, higher tumor mutational load (TMB), greater immune cell infiltration abundance, and enhanced sensitivity to immunotherapy. Lastly, we verified the differential expression of the model gene CD44 using qRT-PCR. In conclusion, our study offers a valuable tool to guide clinical management and targeted therapy of OC.

Integrating multiple machine learning methods to construct glutamine metabolism-related signatures in lung adenocarcinoma

Background

Glutamine metabolism (GM) is known to play a critical role in cancer development, including in lung adenocarcinoma (LUAD), although the exact contribution of GM to LUAD remains incompletely understood. In this study, we aimed to discover new targets for the treatment of LUAD patients by using machine learning algorithms to establish prognostic models based on GM-related genes (GMRGs).

Methods

We used the AUCell and WGCNA algorithms, along with single-cell and bulk RNA-seq data, to identify the most prominent GMRGs associated with LUAD. Multiple machine learning algorithms were employed to develop risk models with optimal predictive performance. We validated our models using multiple external datasets and investigated disparities in the tumor microenvironment (TME), mutation landscape, enriched pathways, and response to immunotherapy across various risk groups. Additionally, we conducted in vitro and in vivo experiments to confirm the role of LGALS3 in LUAD.

Results

We identified 173 GMRGs strongly associated with GM activity and selected the Random Survival Forest (RSF) and Supervised Principal Components (SuperPC) methods to develop a prognostic model. Our model's performance was validated using multiple external datasets. Our analysis revealed that the low-risk group had higher immune cell infiltration and increased expression of immune checkpoints, indicating that this group may be more receptive to immunotherapy. Moreover, our experimental results confirmed that LGALS3 promoted the proliferation, invasion, and migration of LUAD cells.

Conclusion

Our study established a prognostic model based on GMRGs that can predict the effectiveness of immunotherapy and provide novel approaches for the treatment of LUAD. Our findings also suggest that LGALS3 may be a potential therapeutic target for LUAD.

Mast cell marker gene signature: prognosis and immunotherapy response prediction in lung adenocarcinoma through integrated scRNA-seq and bulk RNA-seq

Background

Mast cells, comprising a crucial component of the tumor immune milieu, modulate neoplastic progression by secreting an array of pro- and antitumorigenic factors. Numerous extant studies have produced conflicting conclusions regarding the impact of mast cells on the prognosis of patients afflicted with lung adenocarcinoma (LUAD).

Methods

Employing single-cell RNA sequencing (scRNA-seq) analysis, mast cell-specific marker genes in LUAD were ascertained. Subsequently, a mast cell-related genes (MRGs) signature was devised to stratify LUAD patients into high- and low-risk cohorts based on the median risk value. Further investigations were conducted to assess the influence of distinct risk categories on the tumor microenvironment. The prognostic import and capacity to prognosticate immunotherapy benefits of the MRGs signature were corroborated using four external cohorts. Ultimately, the functional roles of SYAP1 were validated through in vitro experimentation.

Results

After scRNA-seq and bulk RNA-seq data analysis, we established a prognostic signature consisting of nine MRGs. This profile effectively distinguished favorable survival outcomes in both the training and validation cohorts. In addition, we identified the low-risk group as a population more effective for immunotherapy. In cellular experiments, we found that silencing SYAP1 significantly reduced the proliferation, invasion and migratory capacity of LUAD cells while increasing apoptosis.

Conclusion

Our MRGs signature offers valuable insights into the involvement of mast cells in determining the prognosis of LUAD and may prove instrumental as a navigational aid for immunotherapy selection, as well as a predictor of immunotherapy response in LUAD patients.

Imaging diagnosis of intravenous leiomyomatosis: an institutional experience

AIM

To review and summarise the clinical and imaging characteristics of intravenous leiomyomatosis (IVL), a rare smooth muscle tumour originating from the uterus.

MATERIALS AND METHODS

Twenty-seven patients with a histopathological diagnosis of IVL who underwent surgery were reviewed retrospectively. All patients underwent pelvic ultrasonography, inferior vena cava (IVC) ultrasonography, and echocardiography before surgery. Computed tomography (CT) with contrast enhancement was performed in patients with extrapelvic IVL. Some patients underwent pelvic magnetic resonance imaging (MRI).

RESULTS

Mean age was 44.81 years. Clinical symptoms were non-specific. IVL was intrapelvic in seven patients and extrapelvic in 20. Preoperative pelvic ultrasonography missed the diagnosis in 85.7% of patients with intrapelvic IVL. Pelvic MRI was useful to evaluate the parauterine vessels. Incidence of cardiac involvement was 59.26%. Echocardiography showed a highly mobile sessile mass in the right atrium with moderate-to-low echogenicity that originates from the IVC. Ninety per cent of extrapelvic lesions showed unilateral growth. The most common growth pattern was via the right uterine vein-internal iliac vein-IVC pathway.

CONCLUSION

The clinical symptoms of IVL are non-specific. For patients with intrapelvic IVL, early diagnosis is difficult. Pelvic ultrasound should focus on the parauterine vessels, the iliac and ovarian veins should be explored carefully. MRI has obvious advantages in evaluating parauterine vessel involvement, which is helpful for early diagnosis. For patients with extrapelvic IVL, CT should be performed before surgery as part of a comprehensive evaluation. IVC ultrasonography and echocardiography are recommended when IVL is highly suspected.

The integrated single-cell analysis developed a lactate metabolism-driven signature to improve outcomes and immunotherapy in lung adenocarcinoma

Background

It has been suggested that lactate metabolism (LM) is crucial for the development of cancer. Using integrated single-cell RNA sequencing (scRNA-seq) analysis, we built predictive models based on LM-related genes (LMRGs) to propose novel targets for the treatment of LUAD patients.

Methods

The most significant genes for LM were identified through the use of the AUCell algorithm and correlation analysis in conjunction with scRNA-seq analysis. To build risk models with superior predictive performance, cox- and lasso-regression were utilized, and these models were validated on multiple external independent datasets. We then explored the differences in the tumor microenvironment (TME), immunotherapy, mutation landscape, and enriched pathways between different risk groups. Finally, cell experiments were conducted to verify the impact of AHSA1 in LUAD.

Results

A total of 590 genes that regulate LM were identified for subsequent analysis. Using cox- and lasso-regression, we constructed a 5-gene signature that can predict the prognosis of patients with LUAD. Notably, we observed differences in TME, immune cell infiltration levels, immune checkpoint levels, and mutation landscapes between different risk groups, which could have important implications for the clinical treatment of LUAD patients.

Conclusion

Based on LMRGs, we constructed a prognostic model that can predict the efficacy of immunotherapy and provide a new direction for treating LUAD.

Prediction of the Number of Cumulative Pulses Based on the Photon Statistical Entropy Evaluation in Photon-Counting LiDAR

Photon-counting LiDAR encounters interference from background noise in remote target detection, and the statistical detection of the accumulation of multiple pulses is necessary to eliminate the uncertainty of responses from the Geiger-mode avalanche photodiode (Gm-APD). The cumulative number of statistical detections is difficult to select due to the lack of effective evaluation of the influence of the background noise. In this work, a statistical detection signal evaluation method based on photon statistical entropy (PSE) is proposed by developing the detection process of the Gm-APD as an information transmission model. A prediction model for estimating the number of cumulative pulses required for high-accuracy ranging with the background noise is then established. The simulation analysis shows that the proposed PSE is more sensitive to the noise compared with the signal-to-noise ratio evaluation, and a minimum PSE exists to ensure all the range detections with background noise are close to the true range with a low and stable range error. The experiments demonstrate that the prediction model provides a reliable estimation of the number of required cumulative pulses in various noise conditions. With the estimated number of cumulative pulses, when the signal photons are less than 0.1 per pulse, the range accuracy of 4.1 cm and 5.3 cm are obtained under the background noise of 7.6 MHz and 5.1 MHz, respectively.

Single cell sequencing analysis constructed the N7-methylguanosine (m7G)-related prognostic signature in uveal melanoma

BACKGROUND

Uveal melanoma is a highly malignant tumor in the eye. Its recurrence and metastasis are common, and the prognosis is poor.

METHODS

The transcriptome data of UVM were downloaded from TCGA database, and the single cell sequencing dataset GSE139829 was downloaded from GEO database. Weighted co-expression network analysis was used to explore the modules associated with m7G. Lasso regression was used to construct M⁷G-related prognostic signature. Immune infiltration analysis was used to explore the significance of the model in the tumor immune microenvironment. Finally, cell assays were used to explore the function of key genes in the MUM-2B and OCM-1 cell lines of UVM.

RESULTS

The prognostic signature was constructed by Cox regression and Lasso regression. Patients could be divided into high-risk group and low-risk group by this signature, and the high-risk group had worse prognosis (P<0.05). Cell experiments showed that the proliferation, invasion and migration ability of UVM cell lines were significantly decreased after the knockdown of PAG1, a key gene in signature, which proved that PAG1 might be a potential target of UVM.

CONCLUSIONS

Our study explored the significance of m⁷G in UVM, provided biomarkers for its diagnosis and treatment.

Determining the gluonic gravitational form factors of the proton

The proton is one of the main building blocks of all visible matter in the Universe¹. Among its intrinsic properties are its electric charge, mass and spin². These properties emerge from the complex dynamics of its fundamental constituents-quarks and gluons-described by the theory of quantum chromodynamics^3-5. The electric charge and spin of protons, which are shared among the quarks, have been investigated previously using electron scattering². An example is the highly precise measurement of the electric charge radius of the proton⁶. By contrast, little is known about the inner mass density of the proton, which is dominated by the energy carried by gluons. Gluons are hard to access using electron scattering because they do not carry an electromagnetic charge. Here we investigated the gravitational density of gluons using a small colour dipole, through the threshold photoproduction of the J/ψ particle. We determined the gluonic gravitational form factors of the proton^7,8 from our measurement. We used a variety of models^9-11 and determined, in all cases, a mass radius that is notably smaller than the electric charge radius. In some, but not all cases, depending on the model, the determined radius agrees well with first-principle predictions from lattice quantum chromodynamics¹². This work paves the way for a deeper understanding of the salient role of gluons in providing gravitational mass to visible matter.

[Prognostic analysis of acute pulmonary thromboembolism with newly diagnosed atrial fibrillation]

Objective: To analyze the clinical characteristics and to explore the prognostic factors of acute pulmonary embolism(APE) with newly diagnosed atrial fibrillation(AF). Methods: The medical records of inpatients with APE discharged from Beijing Anzhen Hospital between January 1, 2008, and December 31, 2021 were retrospectively reviewed. The clinical symptoms, complications, laboratory results, echocardiographic parameters, simplified pulmonary embolism severity index (sPESI) and adverse in-hospital outcome were compared between the newly diagnosed AF group and the sinus rhythm group. Logistic regression analysis was used to evaluate the risk factors of adverse in-hospital outcome with APE. Results: Fifty-one patients were included in newly diagnosed AF group and 102 cases in the sinus rhythm group. The patients in newly diagnosed AF group had greater sPESI scores, higher proportion of sPESI≥2 scores, higher incidence of adverse in-hospital outcome as well as longer hospital stay days. Newly diagnosed AF and sPESI≥2 scores were independent predictors affecting adverse in-hospital outcome. The area under ROC curve in newly diagnosed AF combined with sPESI≥2 scores was largest. Conclusions: The APE patients with newly diagnosed AF were more severely ill and prone to in-hospital adverse outcome. Newly diagnosed AF was an independent predictor affecting adverse in-hospital outcome. sPESI≥2 combined with newly diagnosed AF scores had a high predictive value for the occurrence of in-hospital adverse outcome.

Construction and validation of the diagnostic model of keloid based on weighted gene co-expression network analysis (WGCNA) and differential expression analysis

Keloid is a disease that seriously affects the aesthetic appearance of the body. In contrast to normal skin or hypertrophic scars, keloid tissue extends beyond the initial site of injury. Patients may complain of pain, itching, or burning. Although multiple treatments exist, none is uniformly successful. Genetic advances have made it possible to explore differences in gene expression between keloids and normal skin. Identifying the biomarker for keloid is beneficial to the mechanism exploration and treatment development of keloid. In this study, we identified seven genes with significant differences in keloids through weighted gene co-expression network analysis(WGCNA) and differential expression analysis. Then, by the Lasso regression, we constructed a keloid diagnostic model using five of these genes. Further studies found that keloids could be divided into high-risk and low-risk groups by this model, with differences in immunity, m6A methylation, and pyroptosis. Finally, we verified the accuracy of the diagnostic model in clinical RNA-sequencing data.

ADM-assisted prepectoral breast reconstruction is not associated with high complication rate as before: a Meta-analysis

Implant-related breast reconstruction can be divided into subpectoral breast reconstruction (SPBR) and prepectoral breast reconstruction (PPBR) according to the different anatomical planes. The previous stereotype was that PPBR had a high complication rate and was not suitable for clinical use. However, with the emergence of acellular dermal matrix (ADM), the clinical effect of PPBR has been improved. To compare the outcomes difference between SPBR and PPBR, We conducted this meta-analysis. Articles on SPBR versus PPBR were searched in PubMed, Web of Sciences, Embase, and Cochrane databases, strictly following the PRISMA guidelines. According to the set criteria, we included the literature that met the requirements. Extracted data were the incidence of adverse events and the duration of drainage. Results show that SPBR has a higher incidence rate in capsular contracture, animation deformity, infection, hematoma and delayed healing wound than PPBR. There are no significant differences in skin flap necrosis, seroma, implant loss, reoperation and duration of drainage between the two groups. Hence, PPBR is no longer a high complication surgical method and can be used in the clinical practice. However, there are few large sample studies at present, so it is necessary to carry out further studies on PPBR.

Advances in Prepectoral Breast Reconstruction

Breast reconstruction can be divided into prepectoral breast reconstruction (PPBR) and subpectoral breast reconstruction (SPBR) according to the implant plane. The original prepectoral breast reconstruction was abandoned for a long time due to the frequent and severe complications. Now, advances in materials technology and improved methods of mastectomy have made safe prepectoral breast reconstruction possible. Moreover, a number of studies have gradually demonstrated the advantages of prepectoral breast reconstruction. As prepectoral breast reconstruction becomes more and more attractive, it is time to review the current advances in prepectoral breast reconstruction.

Factors associated with cardiovascular events after simultaneous liver-kidney transplant from the US Multicenter Simultaneous Liver-Kidney Transplant Consortium

Cardiovascular disease is a leading complication after both liver and kidney transplantation. Factors associated with and rates of cardiovascular events (CVEs) after simultaneous liver-kidney transplant (SLKT) are unknown. This was a retrospective cohort study of adult SLKT recipients between 2002 and 2017 at six centers in six United Network for Organ Sharing regions in the US Multicenter SLKT Consortium. The primary outcome was a CVE defined as hospitalization due to acute coronary syndrome, arrhythmia, congestive heart failure, or other CV causes (stroke or peripheral vascular disease) within 1 year of SLKT. Among 515 SLKT subjects (mean age ± SD, 55.4 ± 10.6 years; 35.5% women; 68.1% White), 8.7% had a CVE within 1 year of SLKT. The prevalence of a CVE increased from 3.3% in 2002-2008 to 8.9% in 2009-2011 to 14.0% in 2012-2017 ( p  = 0.0005). SLKT recipients with a CVE were older (59.9 vs. 54.9 years, p  < 0.0001) and more likely to have coronary artery disease (CAD) (37.8% vs. 18.4%, p  = 0.002) and atrial fibrillation (AF) (27.7% vs. 7.9%, p  = 0.003) than those without a CVE. There was a trend toward older age by era of SLKT ( p  = 0.054). In multivariate analysis adjusted for cardiac risk factors at transplant, age (odds ratio [OR], 1.06; 95% confidence interval [CI], 1.02, 1.11), CAD (OR, 3.62; 95% CI, 1.60, 8.18), and AF (OR, 2.36; 95% CI, 1.14, 4.89) were associated with a 1-year CVE after SLKT. Conclusion : Among SLKT recipients, we observed a 4-fold increase in the prevalence of 1-year CVEs over time. Increasing age, CAD, and AF were the main potential explanatory factors for this trend independent of other risk factors. These findings suggest that CV risk protocols may need to be tailored to this high-risk population.

[New pathological classification and clinical implications of pituitary neuroendocrine tumors of the 2022 WHO version]

In 2022, the World Health Organization proposed a new classification for pituitary adenomas. The major nomenclature change from the previous edition was the transition from"adenoma"to"pituitary neuroendocrine tumor"(PitNETs). The new classification provided the detailed histological subtypes of PitNETs for routine use of antibodies such as pituitary transcription factors (PIT1, TPIT, SF1, GATA3, and ERα) and hormones. The major PIT1, TPIT, and SF1 lineage-defined PitNETs types and subtypes featured distinct morphologic, molecular, and clinical differences. Unlike the 2017 WHO classification, the 2022 WHO version updated some concepts as follows: (1) Mammosomatotroph, acidophil stem cell tumors and mixed somatotroph/lactotroph tumor represented distinct PIT1-lineage PitNETs; (2) The diagnostic category of PIT1-positive plurihormonal tumor was replaced by the immature PIT1-lineage tumor and the mature plurihormonal PIT1-lineage tumor; (3) The term"metastatic PitNET"was advocated to replace the previous terminology"pituitary carcinoma". The new classification emphasizes the importance of pathological classification of PitNETs. Obviously, accurate pathological interpretation is the key to judge the clinical treatment pathway and prognosis of patients.

Hippo signaling instructs ectopic but not normal organ growth

The Hippo signaling pathway is widely considered a master regulator of organ growth because of the prominent overgrowth phenotypes caused by experimental manipulation of its activity. Contrary to this model, we show here that removing Hippo transcriptional output did not impair the ability of the mouse liver and Drosophila eyes to grow to their normal size. Moreover, the transcriptional activity of the Hippo pathway effectors Yap/Taz/Yki did not correlate with cell proliferation, and hyperactivation of these effectors induced gene expression programs that did not recapitulate normal development. Concordantly, a functional screen in Drosophila identified several Hippo pathway target genes that were required for ectopic overgrowth but not normal growth. Thus, Hippo signaling does not instruct normal growth, and the Hippo-induced overgrowth phenotypes are caused by the activation of abnormal genetic programs.