Metal ion levels after metal-on-metal hip resurfacing: A single-center longitudinal study of Chinese patients.

This study aimed to investigate the long-term serum metal ion levels of patients who received metal-on-metal hip resurfacing arthroplasty (MoM HRA). We conducted a retrospective study of 99 patients (110 hips) from March 2006 to May 2017 who underwent MoM HRA. The Harris Hip Score (HHS) and the University of California at Los Angeles (UCLA) activity score were measured, and the patients underwent clinical and radiological management. Serum levels of cobalt (Co), chromium (Cr), and molybdenum (Mo) were measured using inductively coupled plasma mass spectrometry (ICPMS) at 1, 6, and 12 months, and each year follow-up after prosthesis implantation. Patients were followed up from 1 to 156 months, with a mean of 98 months. No complications occurred. Metal ion analysis revealed significantly elevated levels compared to preoperative levels. The metal ions levels increased and reached a peak after surgery, and then the levels began to decline gradually. Approximately 84-108 months after surgery, the metal ion levels increased again to approximately peak levels. Then, up to 156 months after surgery, the metal ions levels will drop approximately to preoperative levels. The serum levels of Cr in women were higher than those in men, with the difference being statistically significant. Patients with a body mass index (BMI) of ≥24.9 kg/m2 Co levels were significantly higher than those of normal-weight patients. The serum levels of metal ions showed no significant differences between the prostheses. The use of the MoM HRA was clinically effective, and the Co, Cr, and Mo levels increased significantly after HRA; however, upon long-term follow-up, serum metal ion levels tended to decrease to preoperative levels. Longer follow-up periods and larger study samples are needed to establish the long-term outcome of patients undergoing HRA with MoM bearings. Level IV, Therapeutic Study.

The m6A writer KIAA1429 regulates photoaging progression via MFAP4-dependent collagen synthesis.

BACKGROUND: N6-Methyladenosine (m6A) methylation, a common form of RNA modification, play an important role in the pathogenesis of various diseases and in the ontogeny of organisms. Nevertheless, the precise function of m6A methylation in photoaging remains unknown. OBJECTIVES: This study aims to investigate the biological role and underlying mechanism of m6A methylation in photoaging. METHODS: m6A dot blot, Real-time quantitative PCR (RT-qPCR), western blot and immunohistochemical (IHC) assays were employed to detect the m6A level and specific m6A methylase in ultraviolet ray (UVR)-induced photoaging tissue. The profile of m6A-tagged mRNA was identified by methylated RNA immunoprecipitation sequencing (MeRIP-seq) and RNA-seq analysis. Finally, we investigated the regulatory mechanism of KIAA1429 by MeRIP-qPCR, RNA knockdown and immunofluorescence assay. RESULTS: m6A levels were increased in photoaging and were closely associated with the upregulation of KIAA1429 expression. 1331 differentially m6A methylated genes were identified in the UVR group compared with the control group, of which 1192 (90%) were hypermethylated. Gene ontology analysis showed that genes with m6A hypermethylation and mRNA downregulation were mainly involved in extracellular matrix metabolism and collagen metabolism-related processes. Furthermore, KIAA1429 knockdown abolished the downregulation of TGF-bRII and upregulation of MMP1 in UVR-irradiated human dermal fibroblasts (HDFs). Mechanically, we identified MFAP4 as a target of KIAA1429-mediated m6A modification and KIAA1429 might suppress collagen synthesis through an m6A-MFAP4-mediated process. CONCLUSIONS: The increased expression of KIAA1429 hinders collagen synthesis during UVR-induced photoaging, suggesting that KIAA1429 represents a potential candidate for targeted therapy to mitigate UVR-driven photoaging.

Quercetin inhibited LPS-induced cytokine storm by interacting with the AKT1-FoxO1 and Keap1-Nrf2 signaling pathway in macrophages.

Cytokine storm (CS) emerges as an exacerbated inflammatory response triggered by various factors such as pathogens and excessive immunotherapy, posing a significant threat to life if left unchecked. Quercetin, a monomer found in traditional Chinese medicine, exhibits notable anti-inflammatory and antiviral properties. This study endeavors to explore whether quercetin intervention could mitigate CS through a combination of network pharmacology analysis and experimental validation. First, common target genes and potential mechanisms affected by quercetin and CS were identified through network pharmacology, and molecular docking experiments confirmed quercetin and core targets. Subsequently, in vitro experiments of Raw264.7 cells stimulated by lipopolysaccharide (LPS) showed that quercetin could effectively inhibit the overexpression of pro-inflammatory mediators and regulate the AKT1-FoxO1 signaling pathway. At the same time, quercetin can reduce ROS through the Keap1-Nrf2 signaling pathway. In addition, in vivo studies of C57BL/6 mice injected with LPS further confirmed quercetin's inhibitory effect on CS. In conclusion, this investigation elucidated novel target genes and signaling pathways implicated in the therapeutic effects of quercetin on CS. Moreover, it provided compelling evidence supporting the efficacy of quercetin in reversing LPS-induced CS, primarily through the regulation of the AKT1-FoxO1 and Keap1-Nrf2 signaling pathways.

Opportunistic Assessment of Hip Fracture Risk Based on Chest CT.

OBJECTIVE: Hip fracture (HF) has been described as the "last fracture of life" in the elderly, so the assessment of HF risk is extremely important. Currently, few studies have examined the relationship between imaging data from chest computed tomography (CT) and HF. This study demonstrated that pectoral muscle index (PMI) and vertebral body attenuation values could predict HF, aiming to opportunistically assess the risk of HF in patients without bone mineral density (BMD) based on chest CT for other diseases. METHODS: In the retrospective study, 800 participants who had both BMD and chest CT were enrolled from January 2021 to January 2024. After exclusion, 472 patients were finally enrolled, divided into the healthy control (HC) group and the HF group. Clinical data were collected, and differences between the two groups were compared. A predictive model was constructed based on the PMI and CT value of the fourth thoracic vertebra (T4HU) by logistic regression analysis, and the predictive effect of the model was analyzed by using the receiver operating characteristic (ROC) curve. Finally, the clinical utility of the model was analyzed using decision curve analysis (DCA) and clinical impact curves. RESULTS: Both PMI and T4HU were lower in the HF group than in the HC group (p < 0.05); low PMI and low T4HU were risk factors for HF. The predictive model incorporating PMI and T4HU on the basis of age and BMI had excellent diagnostic efficacy with an area under the curve (AUC) of 0.865 (95% confidence interval [CI]: 0.830-0.894, p < 0.01), sensitivity and specificity of 0.820 and 0.754, respectively. The clinical utility of the model was validated using calibration curves and DCA. The AUC of the predictive model incorporating BMD based on age and BMI was 0.865 (95% CI: 0.831-0.895, p < 0.01), with sensitivity and specificity of 0.698 and 0.711, respectively. There was no significant difference in diagnostic efficacy between the two models (p = 0.967). CONCLUSIONS: PMI and T4HU are predictors of HF in patients. In the absence of dual-energy x-ray absorptiometry (DXA), the risk of HF can be assessed by measuring the PMI and T4HU on chest CT examination due to other diseases, and further treatment can be provided in time to reduce the incidence of HF.

Contrastive machine learning reveals Parkinson's disease specific features associated with disease severity and progression.

Parkinson's disease (PD) exhibits heterogeneity in terms of symptoms and prognosis, likely due to diverse neuroanatomical alterations. This study employs a contrastive deep learning approach to analyze Magnetic Resonance Imaging (MRI) data from 932 PD patients and 366 controls, aiming to disentangle PD-specific neuroanatomical alterations. The results reveal that these neuroanatomical alterations in PD are correlated with individual differences in dopamine transporter binding deficit, neurodegeneration biomarkers, and clinical severity and progression. The correlation with clinical severity is verified in an external cohort. Notably, certain proteins in the cerebrospinal fluid are strongly associated with PD-specific features, particularly those involved in the immune function. The most notable neuroanatomical alterations are observed in both subcortical and temporal regions. Our findings provide deeper insights into the patterns of brain atrophy in PD and potential underlying molecular mechanisms, paving the way for earlier patient stratification and the development of treatments to slow down neurodegeneration.

Building a predictive model for depression risk in fracture patients: insights from cross-sectional NHANES 2005-2020 data and an external hospital-based dataset.

BACKGROUND: Depression represents a frequent mental health challenge in individuals with fractures, negatively impacting their recuperation and overall well-being. The purpose of this research was to formulate and corroborate a prognostic framework for pinpointing depression risk among fracture sufferers by utilizing data from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2020 and a separate hospital-based group. METHODS: We analyzed records from 1,748 individuals with fractures documented in the NHANES database spanning 2005 to 2020, of which 362 were diagnosed with depression, as indicated by a Patient Health Questionnaire-9 (PHQ-9) score of 10 or higher. An additional validation group comprised 360 fracture patients sourced from a medical center. Considered variables for prediction encompassed demographic details, lifestyle habits, past medical conditions, and laboratory results. The method of least absolute shrinkage and selection operator (LASSO) regression facilitated the narrowing down of variables, while multivariate logistic regression was employed to pinpoint significant predictors. To assist in prediction, a nomogram was designed and subsequently validated. RESULTS: Five independent predictors were identified: drinking, insomnia, poverty-to-income ratio, education level, and white blood cell count. The nomogram showed good discrimination in the NHANES cohorts (training area under the curve (AUC) 0.734, validation AUC 0.740) and hospital-based external validation (AUC 0.711). Calibration curves and decision analysis supported its predictive accuracy and clinical value. CONCLUSION: The constructed nomogram offers a precise and clinically relevant instrument for forecasting depression risk in patients with fractures, facilitating the early detection of individuals at high risk and enabling prompt intervention.

The delivery of PD-L1 siRNA by neutrophil-targeted lipid nanoparticles effectively ameliorates sepsis.

BACKGROUND: Sepsis, a complex and life-threatening disease, poses a significant global burden affecting over 48 million individuals. Recently, it has been reported that programmed death-ligand 1 (PD-L1) expressed on neutrophils is involved in both inflammatory organ dysfunction and immunoparalysis in sepsis. However, there is a dearth of strategies to specifically target PD-L1 in neutrophils in vivo. METHODS: We successfully developed two lipid nanoparticles (LNPs) specifically targeting neutrophils by delivering PD-L1 siRNA via neutrophil-specific antibodies and polypeptides. In vivo and in vitro experiments were performed to detect lipid nanoparticles into neutrophils. A mouse cecal ligation and puncture (CLP) model was used to detect neutrophil migration, neutrophil extracellular traps (NETs) level, and organ damage. RESULT: The PD-L1 siRNA-loaded LNPs that target neutrophils suppressed inflammation, reduced the release of NETs, and inhibited T-lymphocyte apoptosis. This approach could help maintain homeostasis of both the immune and inflammatory responses during sepsis. Furthermore, the PD-L1 siRNA-loaded LNPs targeting neutrophils have the potential to ameliorate the multi-organ damage and lethality resulting from CLP. CONCLUSIONS: Taken together, our data identify a previously unknown drug delivery strategy targeting neutrophils, which represents a novel, safe, and effective approach to sepsis therapy.

Predictive value of ultrasound diagnosis of aberrant right subclavian artery with non-recurrent laryngeal nerve.

Introduction: This study aims to evaluate the predictive value of color Doppler ultrasound for the diagnosis of aberrant right subclavian artery (ARSA) with a co-occurring non-recurrent right laryngeal nerve (NRLN). Material and methods: In the present study, 58 patients with ARSA (ARSA group) and 1,280 patients without ARSA (controls) were diagnosed by ultrasonography. In addition, 32 patients with ARSA (ARSA operation group) and controls underwent thyroidectomy with surgical exploration with or without NRLN. Then, the incidence of NRLN was analyzed. The right common carotid artery (RCCA) and right subclavian artery (RSA) trends were observed by ultrasound, and classified into two types: RCCA and RSA originating from the innominate artery (IA) (type I), and IA could not be detected (type II). Results: A total of 32 cases of NRLN were found in the ARSA operation group, but no case was found in controls, and the difference was statistically significant (p = 0.0006). The difference in the constituent ratio of type I and type II was statistically significant between the ARSA group and controls (p = 0.0002). That is, the IA could not be detected in the ARSA group, which was accompanied by the RCCA that originated from the aortic arch, while the IA was detected in most patients in the control group at the level of the sternoclavicular joints. Conclusions: Aberrant right subclavian artery can be rapidly detected by ultrasonography. Aberrant right subclavian artery occurs when the RCCA originates from the aortic arch during detection. Patients with ARSA sometimes have co-occurring NRLN. Hence, vigilance in protecting the NRLN is needed during an operation.

Multiplex cerebrospinal fluid proteomics identifies biomarkers for diagnosis and prediction of Alzheimer's disease.

Recent expansion of proteomic coverage opens unparalleled avenues to unveil new biomarkers of Alzheimer's disease (AD). Among 6,361 cerebrospinal fluid (CSF) proteins analysed from the ADNI database, YWHAG performed best in diagnosing both biologically (AUC = 0.969) and clinically (AUC = 0.857) defined AD. Four- (YWHAG, SMOC1, PIGR and TMOD2) and five- (ACHE, YWHAG, PCSK1, MMP10 and IRF1) protein panels greatly improved the accuracy to 0.987 and 0.975, respectively. Their superior performance was validated in an independent external cohort and in discriminating autopsy-confirmed AD versus non-AD, rivalling even canonical CSF ATN biomarkers. Moreover, they effectively predicted the clinical progression to AD dementia and were strongly associated with AD core biomarkers and cognitive decline. Synaptic, neurogenic and infectious pathways were enriched in distinct AD stages. Mendelian randomization did not support the significant genetic link between CSF proteins and AD. Our findings revealed promising high-performance biomarkers for AD diagnosis and prediction, with implications for clinical trials targeting different pathomechanisms.

Whole exome sequencing analysis identifies genes for alcohol consumption.

Alcohol consumption is a heritable behavior seriously endangers human health. However, genetic studies on alcohol consumption primarily focuses on common variants, while insights from rare coding variants are lacking. Here we leverage whole exome sequencing data across 304,119 white British individuals from UK Biobank to identify protein-coding variants associated with alcohol consumption. Twenty-five variants are associated with alcohol consumption through single variant analysis and thirteen genes through gene-based analysis, ten of which have not been reported previously. Notably, the two unreported alcohol consumption-related genes GIGYF1 and ANKRD12 show enrichment in brain function-related pathways including glial cell differentiation and are strongly expressed in the cerebellum. Phenome-wide association analyses reveal that alcohol consumption-related genes are associated with brain white matter integrity and risk of digestive and neuropsychiatric diseases. In summary, this study enhances the comprehension of the genetic architecture of alcohol consumption and implies biological mechanisms underlying alcohol-related adverse outcomes.

Linking fatty liver diseases to hepatocellular carcinoma by hepatic stellate cells.

Hepatic stellate cells (HSCs), a distinct category of non-parenchymal cells in the liver, are critical for liver homeostasis. In healthy livers, HSCs remain non-proliferative and quiescent. However, under conditions of acute or chronic liver damage, HSCs are activated and participate in the progression and regulation of liver diseases such as liver fibrosis, cirrhosis, and liver cancer. Fatty liver diseases (FLD), including nonalcoholic (NAFLD) and alcohol-related (ALD), are common chronic inflammatory conditions of the liver. These diseases, often resulting from multiple metabolic disorders, can progress through a sequence of inflammation, fibrosis, and ultimately, cancer. In this review, we focused on the activation and regulatory mechanism of HSCs in the context of FLD. We summarized the molecular pathways of activated HSCs (aHSCs) in mediating FLD and their role in promoting liver tumor development from the perspectives of cell proliferation, invasion, metastasis, angiogenesis, immunosuppression, and chemo-resistance. We aimed to offer an in-depth discussion on the reciprocal regulatory interactions between FLD and HSC activation, providing new insights for researchers in this field.

Prediction of Future Parkinson Disease Using Plasma Proteins Combined With Clinical-Demographic Measures.

BACKGROUND AND OBJECTIVES: Identification of individuals at high risk of developing Parkinson disease (PD) several years before diagnosis is crucial for developing treatments to prevent or delay neurodegeneration. This study aimed to develop predictive models for PD risk that combine plasma proteins and easily accessible clinical-demographic variables. METHODS: Using data from the UK Biobank (UKB), which recruited participants across the United Kingdom, we conducted a longitudinal study to identify predictors for incident PD. Participants with baseline plasma proteins and no PD were included. Through machine learning, we narrowed down predictors from a pool of 1,463 plasma proteins and 93 clinical-demographic. These predictors were then externally validated using the Parkinson's Progression Marker Initiative (PPMI) cohort. To further investigate the temporal trends of predictors, a nested case-control study was conducted within the UKB. RESULTS: A total of 52,503 participants without PD (median age 58, 54% female) were included. Over a median follow-up duration of 14.0 years, 751 individuals were diagnosed with PD (median age 65, 37% female). Using a forward selection approach, we selected a panel of 22 plasma proteins for optimal prediction. Using an ensemble tree-based Light Gradient Boosting Machine (LightGBM) algorithm, the model achieved an area under the receiver operating characteristic curve (AUC) of 0.800 (95% CI 0.785-0.815). The LightGBM prediction model integrating both plasma proteins and clinical-demographic variables demonstrated enhanced predictive accuracy, with an AUC of 0.832 (95% CI 0.815-0.849). Key predictors identified included age, years of education, history of traumatic brain injury, and serum creatinine. The incorporation of 11 plasma proteins (neurofilament light, integrin subunit alpha V, hematopoietic PGD synthase, histamine N-methyltransferase, tubulin polymerization promoting protein family member 3, ectodysplasin A2 receptor, Latexin, interleukin-13 receptor subunit alpha-1, BAG family molecular chaperone regulator 3, tryptophanyl-TRNA synthetase, and secretogranin-2) augmented the model's predictive accuracy. External validation in the PPMI cohort confirmed the model's reliability, producing an AUC of 0.810 (95% CI 0.740-0.873). Notably, alterations in these predictors were detectable several years before the diagnosis of PD. DISCUSSION: Our findings support the potential utility of a machine learning-based model integrating clinical-demographic variables with plasma proteins to identify individuals at high risk for PD within the general population. Although these predictors have been validated by PPMI, additional validation in a more diverse population reflective of the general community is essential.

Identifying behaviour-related and physiological risk factors for suicide attempts in the UK Biobank.

Suicide is a global public health challenge, yet considerable uncertainty remains regarding the associations of both behaviour-related and physiological factors with suicide attempts (SA). Here we first estimated polygenic risk scores (PRS) for SA in 334,706 UK Biobank participants and conducted phenome-wide association analyses considering 2,291 factors. We identified 246 (63.07%) behaviour-related and 200 (10.41%, encompassing neuroimaging, blood and metabolic biomarkers, and proteins) physiological factors significantly associated with SA-PRS, with robust associations observed in lifestyle factors and mental health. Further case-control analyses involving 3,558 SA cases and 149,976 controls mirrored behaviour-related associations observed with SA-PRS. Moreover, Mendelian randomization analyses supported a potential causal effect of liability to 58 factors on SA, such as age at first intercourse, neuroticism, smoking, overall health rating and depression. Notably, machine-learning classification models based on behaviour-related factors exhibited high discriminative accuracy in distinguishing those with and without SA (area under the receiver operating characteristic curve 0.909 ± 0.006). This study provides comprehensive insights into diverse risk factors for SA, shedding light on potential avenues for targeted prevention and intervention strategies.

UBE2D1 promotes glioblastoma proliferation by modulating p21 ubiquitination.

Glioblastoma (GBM) cells exhibit aberrant proliferative abilities and resistance to conventional therapies. However, the mechanisms underlying these malignant phenotypes are poorly understood. In this study, we identified ubiquitin-conjugating enzyme E2D1 (UBE2D1) as a crucial stimulator of GBM development. It is highly expressed in GBM and closely associated with poor prognosis in patients with GBM. UBE2D1 knockdown inhibits GBM cell growth and leads to G1 cell cycle arrest. Mechanistically, UBCH5A binds to p21 at the protein level and induces the ubiquitination and degradation of p21. This negative regulation is mediated by STUB1. Our findings are the first to identify UBE2D1 as a key driver of GBM growth and provide a potential target for improving prognosis and therapy.

Shift work effects on incident neuropsychiatric disorders and shift work tolerance.

BACKGROUND: Shift work is associated with susceptibility to several neuropsychiatric disorders. This study aims to investigate the effect of shift work on the incidence of neuropsychiatric disorders, and highlighting how individual variability may influence the association. METHODS: UK Biobank participants with employment information were included. Cox survival was conducted in main and subgroup analyses. Correlation analyses explored the impact of shift work on brain structures, and mediation analyses were performed to elucidate the shared underlying mechanisms. Shift work tolerance was evaluated through survival analyses contrasting the risks associated with five neuropsychiatric disorders in shift versus non-shift workers across different demographic or occupational strata. RESULTS: The analysis encompassed 254,646 participants. Shift work was associated with higher risk of dementia (HR 1.29, 95 % CI 1.10-1.52), anxiety (1.08, 1.01-1.15), depression (1.29, 1.22-1.36), and sleep disorders (1.18, 1.09-1.28), but not stroke (p = 0.20). Shift work was correlated with decreasing volume of various brain regions, particularly in thalamus, lateral orbitofrontal, and middle temporal. Mediation analysis revealed that increased immune response and glucose levels are common pathways linking shift work to these disorders. We observed diversity in shift work tolerance across different individual characteristics, among which socioeconomic status and length of working hours were the most essential. LIMITATIONS: Self-reported employment information may cause misclassification and recall bias. And since we focused on the middle-aged population, the conclusions may not be representative of younger or older populations. CONCLUSIONS: Our findings indicated the need to monitor shift worker health and provide personalized management to help adapt to shift work.

Clinical practice of the transrectal shear-wave elastography in benign prostatic hyperplasia.

OBJECTIVE: To investigate the practical value of the transrectal two-dimensional shear-wave elastography (SWE) in benign prostatic hyperplasia (BPH). METHODS: Consecutive male participants with and without BPH constituted the BPH and control group respectively were enrolled prospectively between March and December 2022. Transrectal conventional ultrasound and SWE examinations for the prostate were performed on these participants. Data of quantitative stiffness of the transitional zone (TZ) and peripheral zone (PZ) of prostate, volume of prostate (VP) and volume of TZ (VTZ) and prostate specific androgen (PSA), etc., were collected. Linear regression analyses were used to investigate the associations between quantitative stiffness data and other clinical parameters. RESULTS: There were 200 participants evaluated, including 100 healthy participants and 100 BPH patients. For every one-year increment in age, it was correlated with 0.50 kPa increasement of TZ stiffness. VP and VTZ were correlated with TZ stiffness. Higher TZ stiffness was associated with higher free prostate specific antigen (PSA) and total PSA. CONCLUSIONS: The prostate is stiffer and larger in BPH group compared to control group. Quantitative stiffness of the TZ was related with age, VP, VTZ and PSA.

Vertebral HU value and the pectoral muscle index based on chest CT can be used to opportunistically screen for osteoporosis.

BACKGROUND: Existing studies have shown that computed tomography (CT) attenuation and skeletal muscle tissue are strongly associated with osteoporosis; however, few studies have examined whether vertebral HU values and the pectoral muscle index (PMI) measured at the level of the 4th thoracic vertebra (T4) are strongly associated with bone mineral density (BMD). In this study, we demonstrate that vertebral HU values and the PMI based on chest CT can be used to opportunistically screen for osteoporosis and reduce fracture risk through prompt treatment. METHODS: We retrospectively evaluated 1000 patients who underwent chest CT and DXA scans from August 2020-2022. The T4 HU value and PMI were obtained using manual chest CT measurements. The participants were classified into normal, osteopenia, and osteoporosis groups based on the results of dual-energy X-ray (DXA) absorptiometry. We compared the clinical baseline data, T4 HU value, and PMI between the three groups of patients and analyzed the correlation between the T4 HU value, PMI, and BMD to further evaluate the diagnostic efficacy of the T4 HU value and PMI for patients with low BMD and osteoporosis. RESULTS: The study ultimately enrolled 469 participants. The T4 HU value and PMI had a high screening capacity for both low BMD and osteoporosis. The combined diagnostic model-incorporating sex, age, BMI, T4 HU value, and PMI-demonstrated the best diagnostic efficacy, with areas under the receiver operating characteristic curve (AUC) of 0.887 and 0.892 for identifying low BMD and osteoporosis, respectively. CONCLUSIONS: The measurement of T4 HU value and PMI on chest CT can be used as an opportunistic screening tool for osteoporosis with excellent diagnostic efficacy. This approach allows the early prevention of osteoporotic fractures via the timely screening of individuals at high risk of osteoporosis without requiring additional radiation.

The safety and efficacy of five surgical treatments in prostate enucleation: a network meta-analysis.

PURPOSE: The aim of our study was to investigate the comparative outcomes of five different energy types on surgical efficacy and postoperative recovery in patients with benign prostate hyperplasia. METHODS: The literature was systematically reviewed on December 1st, 2023, encompassing studies retrieved from PubMed, Embase, Web of Science, and The Cochrane Library databases that incorporated clinical studies of holmium laser enucleation of the prostate (HoLEP), Thulium:YAG laser enucleation of the prostate (ThuLEP), transurethral plasmakinetic enucleation of prostate (PKEP), diode laser enucleation of the prostate (DiLEP) and thulium fiber laser enucleation of the prostate (ThuFLEP) in the treatment of prostatic hyperplasia. Two independent reviewers extracted study data and conducted quality assessments using the Cochrane Collaboration's Risk of Bias tool and Newcastle-Ottawa Scale (NOS). Network meta-analysis (NMA) was employed to indirectly analyze the outcomes of endoscopic enucleation of the prostate (EEP) techniques. RESULTS: The study included a total of 38 studies, comprising 21 non-randomized controlled trials (nRCTs) and 17 randomized controlled trials (RCTs), incorporating five distinct techniques: holmium laser, Thulium:YAG laser, bipolar plasma, diode laser and thulium fiber laser. In comparing treatment durations, ThuLEP and HoLEP had shorter overall hospital stays than PKEP, while the enucleation time of ThuLEP and HoLEP was shorter than that of ThuFLEP. Moreover, the enucleation tissue weight of both thulium fiber laser and holmium laser was heavier than bipolar plasma. However, the analysis did not reveal any statistically significant variation in complications among the various types of enucleation. In postoperative follow-up, the IPSS at 3 months post-operation was superior in the Thulium:YAG laser group compared to the holmium laser group. The thulium fiber laser technique demonstrated significant advantages over other enucleation methods in terms of QoL and PVR at 12 months after surgery. CONCLUSION: Theoretical properties may vary among different energy sources; however, there are no discernible clinical differences in operation-related parameters, postoperative complications, and postoperative follow-up. Therefore, the choice of laser does not significantly impact the outcome. However, due to the limited number of included studies, future research should focus on larger sample sizes and multicenter investigations to further validate the findings of this study.

Survey of Heterodera glycines population abundance and virulence phenotypes during 2021-2022 in Heilongjiang Province.

Soybean cyst nematode (SCN), Heterodera glycines, poses a significant threat to global soybean production. Heilongjiang, the largest soybean-producing province in China, contributes over 40% to the country's total yield. This province has much longer history of SCN infestation. To assess the current situation in Heilongjiang, we conducted a survey to determine the SCN population density and virulence phenotypes during 2021-2022 and compared the data with a previous study in 2015. A total of 377 soil samples from 48 counties representing eleven major soybean-planting regions were collected. The prevalence of SCN increased from 55.4% in 2015 to 59% in the current survey. The population densities ranged from 80 to 26,700 eggs and juveniles per 100 cm3 of soil. Virulence phenotypes were evaluated for 60 representative SCN populations using the HG type test, revealing nine different HG types. The most common virulence phenotypes were HG types 7 and 0, accounting for 56.7% and 20% of all SCN populations, respectively. The prevalence of populations with a reproductive index (FI) greater than 10% on PI548316 increased from 64.5% in 2015 to 71.7%. However, the FI on the commonly used resistance sources PI 548402 (Peking) and PI 437654 remained low at 3.3%. These findings highlight the increasing prevalence and changing virulence phenotypes of SCN in Heilongjiang. They also emphasize the importance of rotating soybean varieties with different resistance sources and urgently identifying new sources of resistance to combat SCN.