Muscle structure predictors of vertical jump performance in elite male volleyball players: a cross-sectional study based on ultrasonography.

Objective: The objective of this investigation is to examine the contribution of key muscle groups in the lower limbs to vertical jumping performance in elite male volleyball players. Specifically, the study focuses on the rectus femoris (RF), vastus lateralis (VL), and lateral gastrocnemius (LG), as well as exploring differences between attack jump and other vertical jump types. Methods: To achieve this, we employed B-mode ultrasound to evaluate the anatomical cross-sectional area (ACSA), muscle thickness (MT), pennation angle (PA), and fascicle length (FL) of the RF, VL, and LG in the participants. Fifteen elite male volleyball players were recruited as participants for this study. Jump heights were measured for four types of vertical jumps: attack jump (AJ), countermovement jump (CMJ), squat jump (SJ), and drop jump (DJ). We conducted regression analyses to assess whether the previously mentioned muscle structures could predict jump performance. Results: Our findings reveal that the muscle structure of the RF does not exhibit any significant correlation with the height of any jump. However, VL-ACSA displays a significant and the most potent predictive effect on jump height for all four jump types (AJ: R 2 = 0.32, p = 0.001; CMJ: R 2 = 0.37, p = 0.005; SJ: R 2 = 0.52, p = 0.001; DJ: R 2 = 0.25, p = 0.021). Conversely, LG-FL only demonstrates a significant and stronger predictive effect on AJ jump height (R 2 = 0.18, p = 0.009). Combining VL-ACSA, LG-FL, and training age through multiple linear regression analysis resulted in a highly significant model for predicting AJ jump height (F = 13.86, R 2 = 0.73). Moreover, the model incorporating VL-ACSA and training age is also important for predicting CMJ, SJ, and DJ jump heights (F = 8.41, R 2 = 0.51; F = 13.14, R 2 = 0.63; F = 5.95, R 2 = 0.41; respectively). Conclusion: The muscle structure indicators in the lower limbs significantly predict jump performance among elite male volleyball players. However, different jump types are influenced by distinct indicators, particularly in the case of AJ, which is associated with LG-FL. This suggests that enhancing LG-FL may positively impact AJ ability, thereby emphasizing the importance of specificity in training. To optimize specialized jump performance in volleyball players, practitioners are advised to assess VL-ACSA and LG-FL and incorporate step-up and eccentric strength training targeting the calf muscles to yield considerable benefits.

Native T1 mapping-based radiomics diagnosis of kidney function and renal fibrosis in chronic kidney disease.

Chronic kidney disease (CKD) raises major concerns for global public health as it is characterized by high prevalence, low awareness, high healthcare costs, and poor prognosis. Therefore, our study prospectively established and validated native T1 mapping-based radiomics models for the prediction of renal fibrosis and renal function in patients with CKD. Moreover, the area under the receiver operating characteristic curve (AUC) and diagnostic sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were used to evaluate its performance. Thus, our results show that radiomics based on native T1 mapping images can better identify renal function and renal fibrosis in patients with CKD and outperform conventional T1 mapping parameters of ΔT1 and T1%, thus providing more information for CKD management and clinical decision-making.

Epigenetic and oncogenic inhibitors cooperatively drive differentiation and kill KRAS-mutant colorectal cancers.

Current treatments for KRAS-mutant colorectal cancers (CRCs) are often limited by cellular plasticity and rewiring responses. Here we describe a promising therapeutic strategy that simultaneously targets epigenetic and oncogenic signals. Specifically, we show that inhibitors of the histone methyltransferase, EZH2, synergize with various RAS pathway inhibitors and promote dramatic tumor regression in vivo. Together these agents cooperatively suppress WNT-driven transcription and drive CRCs into a more differentiated cell state by inducing the Groucho/TLE corepressor, TLE4, along with a network of WNT pathway inhibitors and intestinal differentiation proteins. However, these agents also induce the pro-apoptotic protein BMF, which subsequently kills these more differentiated cells. Accordingly, cell death can be prevented by activating ß-catenin, blocking differentiation, or by ablating BMF expression. Collectively, these studies reveal a new therapeutic approach for treating KRAS-mutant CRCs and illustrate a critical convergence of EZH2 and RAS on oncogenic WNT signals, intestinal differentiation, and apoptosis.

Reduction of Glyoxalase 1 Expression Links Fetal Methylmercury Exposure to Autism Spectrum Disorder Pathogenesis.

Glyoxalase 1 (Glo1) is an essential enzyme to detoxify methylglyoxal (MGO), a cytotoxic byproduct of glycolysis. Accumulating studies have shown an important role of Glo1 in regulating cortical development and neurogenesis, potentially contributing to the pathogenesis of autism spectrum disorder (ASD) when impaired. We have previously shown that prenatal exposure to non-apoptotic low-dose methylmercury (MeHg), an environmental pollutant, induces premature cortical neurogenesis and ASD-like behaviors in a rodent model. In this study, we aimed to determine the underlying molecular mechanisms that mediate prenatal MeHg-induced premature neuronal differentiation and abnormal neurodevelopment. Using single-cell RNA sequencing (scRNA-seq) and real-time quantitative PCR (RT-qPCR), we found that prenatal MeHg exposure at a non-apoptotic dose significantly reduced Glo1 gene expression in embryonic cultured radial glia precursors (RGPs). In cultured RGPs, the knockdown of Glo1 expression increased neuronal production at the expense of the cultured RGPs population, while overexpression of Glo1 restored MeHg-induced neuronal differentiation back to normal levels. Furthermore, we found that co-treatment with both MeHg and multiple MGO scavengers or a CREB inhibitor (iCREB) mitigated MeHg-induced premature neuronal differentiation, reinforcing the role of Glo1 and CREB in mediating MeHg-induced neuronal differentiation. Our findings demonstrate a direct link between MeHg exposure and expression of an ASD risk gene Glo1 in cortical development, supporting the important role of gene-environment interaction in contributing to the etiology of neural developmental disorders, such as ASD.

Comparing the Early Changes in Classified Higher-Order Aberrations Before and After Non-Toric and Toric Implantable Collamer Lens V4c Implantation.

PURPOSE: This study aimed to compare early changes in classified higher-order aberrations (HOAs) pre- and postsurgery in patients who received nontoric versus toric implantable collamer lenses (ICL; ICL Model V4c; STAAR Surgical, Monrovia, CA, USA). METHODS: This prospective study included 124 eyes of 64 patients: 49 eyes were treated using a nontoric implantable collamer lens (ICL), and 75 eyes were treated using a toric implantable collamer lenses (TICL). Refractive parameters and ocular aberrations were examined before and 1 month after surgery. RESULTS: At one month, the safety indices were 1.24 ± 0.17 in the ICL group and 1.20 ± 0.25 in the TICL group (p = 0.39). The efficacy indices were 1.07 ± 0.17 in the ICL group and 1.15 ± 0.26 in the TICL group (p = 0.02). The root mean square (RMS) values of whole-eye total HOAs, trefoil, corneal total HOAs, spherical aberration, and intraocular spherical aberration significantly increased postoperatively in both groups. The RMS of intraocular total HOAs in the TICL group significantly increased 1 month postoperatively. No statistically significant differences were observed in HOA changes between the ICL and TICL groups. CONCLUSIONS: The dominant increases in short-term aberrations after ICL and TICL V4c implantation were in corneal trefoil and intraocular spherical aberrations, which were related to the corneal incision and implanted lens. The HOA changes post-surgery were not statistically different between the two lens types.

Advancing illicit connection diagnosis of urban stormwater pipes: Comprehensive analysis with EEM fluorescence spectroscopy.

Urban drainage systems are significant contributors to the issue of black-odorous water bodies. The current application of stormwater pipe inspection technologies faces substantial limitations, especially in industrial areas with diverse wastewater. This study introduced an innovative approach using excitation-emission matrix (EEM) fluorescence spectroscopy for rapid and accurate diagnosis, providing a new perspective for diagnosing illicit connections. In single wastewater-type areas like residential zones, the method achieved a remarkable 91.5 % accuracy solely through spectra observation and fluorescence peak intensity comparison, outperforming conventional NH3-N-based techniques, which reached an accuracy of only 68.1 %. For regions with complex wastewater scenarios, after EEM subtraction, the residual spectra can be roughly categorized into four distinctive categories based on characteristics. This provides a preliminary assessment and helps in initially identifying the types and sources of inflowing wastewater. Furthermore, the least squares (LS) method refines diagnosis results, offering calculated coefficients reflecting the probability and severity of suspected wastewater intrusion. Simulation experiments and field sample analyses validated the feasibility and accuracy of the EEM-based method, highlighting its advantages for diagnosing illicit connections in both single and mixed wastewater scenarios. The results can significantly narrow down the investigation scope and enhance the confirmation of wastewater sources, exhibiting promising application prospects.

Independent Correlates of Glycemic Control among Adults with Diabetes in South Africa.

BACKGROUND: Globally, the prevalence of diabetes is increasing, especially in low- and middle-income countries (LMICs), including those in the sub-Saharan African region. However, the independent socioeconomic correlates of glycemic control as measured by hemoglobin A1C have yet to be identified. Therefore, the aim of this analysis was to understand the independent correlates of glycemic control in South Africa. METHODS: Data from the 2016 South Africa Demographic and Health Survey on adults with diabetes were used for this analysis. The dependent variable, glycemic control, was defined using hemoglobin A1c (HbA1c). Independent variables included: age, gender, ethnicity, marital status, region, urban/rural residence, ability to read, education, insurance, wealth, occupation, and employment in the last year. Analysis of variance was used to test for differences in mean HbA1c for each category of all independent variables, and a fully adjusted linear regression model was used to identify independent correlates of glycemic control (HbA1c). RESULTS: Among the 772 people included in this analysis, there were significant differences in mean HbA1c by age (p < 0.001), ethnicity (p < 0.001), place of residence (p = 0.024), wealth index (p = 0.001), and employment in the last year (p = 0.008). Independent correlates of HbA1c included age, ethnicity, and wealth index. CONCLUSIONS: This study used data from a large diverse population with a high prevalence of diabetes in sub-Saharan Africa and provides new evidence on the correlates of glycemic control and potential targets for interventions designed to lower HbA1c and improve diabetes-related health outcomes of adults in South Africa.

Advances in Ferroptosis-Inducing Agents by Targeted Delivery System in Cancer Therapy.

Currently, cancer remains one of the most significant threats to human health. Treatment of most cancers remains challenging, despite the implementation of diverse therapies in clinical practice. In recent years, research on the mechanism of ferroptosis has presented novel perspectives for cancer treatment. Ferroptosis is a regulated cell death process caused by lipid peroxidation of membrane unsaturated fatty acids catalyzed by iron ions. The rapid development of bio-nanotechnology has generated considerable interest in exploiting iron-induced cell death as a new therapeutic target against cancer. This article provides a comprehensive overview of recent advancements at the intersection of iron-induced cell death and bionanotechnology. In this respect, the mechanism of iron-induced cell death and its relation to cancer are summarized. Furthermore, the feasibility of a nano-drug delivery system based on iron-induced cell death for cancer treatment is introduced and analyzed. Secondly, strategies for inducing iron-induced cell death using nanodrug delivery technology are discussed, including promoting Fenton reactions, inhibiting glutathione peroxidase 4, reducing low glutathione levels, and inhibiting system Xc-. Additionally, the article explores the potential of combined treatment strategies involving iron-induced cell death and bionanotechnology. Finally, the application prospects and challenges of iron-induced nanoagents for cancer treatment are discussed.

Life-cycle and economic assessments of microalgae biogas production in suspension and biofilm cultivation systems.

Biogas production via anaerobic digestion is highly attractive for microalgae. The technology of microalgae cultivation has profound impacts on biogas production system as it is the most energy-consuming process. However, a comprehensive evaluation of the environmental and economic benefits of different cultivation systems has yet to be sufficiently conducted. Here, life-cycle and economic assessments of open raceway ponds, photobioreactors and biofilm systems were investigated. Results showed greenhouse gas emissions of all systems were positive because more than two-thirds of carbon in fuel gas was lost and the fixed carbon in product gas and solid fertilizer was less than the emitted carbon during energy input. Particularly, biofilm system achieved the least greenhouse gas emissions (9.3 g CO2-eq/MJ), net energy ratio (0.7) and levelized cost of energy (0.9 $/kWh), indicating the optimum cultivation system. Open raceway ponds and photobioreactors failed to achieve positive benefits because of low harvesting efficiency and biomass concentration.

TME-Related Biomimetic Strategies Against Cancer.

The tumor microenvironment (TME) plays an important role in various stages of tumor generation, metastasis, and evasion of immune monitoring and treatment. TME targeted therapy is based on TME components, related pathways or active molecules as therapeutic targets. Therefore, TME targeted therapy based on environmental differences between TME and normal cells has been widely studied. Biomimetic nanocarriers with low clearance, low immunogenicity, and high targeting have enormous potential in tumor treatment. This review introduces the composition and characteristics of TME, including cancer­associated fibroblasts (CAFs), extracellular matrix (ECM), tumor blood vessels, non-tumor cells, and the latest research progress of biomimetic nanoparticles (NPs) based on TME. It also discusses the opportunities and challenges of clinical transformation of biomimetic nanoparticles.

Patient-Specific Heart Geometry Modeling for Solid Biomechanics Using Deep Learning.

Automated volumetric meshing of patient-specific heart geometry can help expedite various biomechanics studies, such as post-intervention stress estimation. Prior meshing techniques often neglect important modeling characteristics for successful downstream analyses, especially for thin structures like the valve leaflets. In this work, we present DeepCarve (Deep Cardiac Volumetric Mesh): a novel deformation-based deep learning method that automatically generates patient-specific volumetric meshes with high spatial accuracy and element quality. The main novelty in our method is the use of minimally sufficient surface mesh labels for precise spatial accuracy and the simultaneous optimization of isotropic and anisotropic deformation energies for volumetric mesh quality. Mesh generation takes only 0.13 seconds/scan during inference, and each mesh can be directly used for finite element analyses without any manual post-processing. Calcification meshes can also be subsequently incorporated for increased simulation accuracy. Numerous stent deployment simulations validate the viability of our approach for large-batch analyses. Our code is available at https://github.com/danpak94/Deep-Cardiac-Volumetric-Mesh.

2D and 3D multiplexed subcellular profiling of nuclear instability in human cancer.

Nuclear atypia, including altered nuclear size, contour, and chromatin organization, is ubiquitous in cancer cells. Atypical primary nuclei and micronuclei can rupture during interphase; however, the frequency, causes, and consequences of nuclear rupture are unknown in most cancers. We demonstrate that nuclear envelope rupture is surprisingly common in many human cancers, particularly glioblastoma. Using highly-multiplexed 2D and super-resolution 3D-imaging of glioblastoma tissues and patient-derived xenografts and cells, we link primary nuclear rupture with reduced lamin A/C and micronuclear rupture with reduced lamin B1. Moreover, ruptured glioblastoma cells activate cGAS-STING-signaling involved in innate immunity. We observe that local patterning of cell states influences tumor spatial organization and is linked to both lamin expression and rupture frequency, with neural-progenitor-cell-like states exhibiting the lowest lamin A/C levels and greatest susceptibility to primary nuclear rupture. Our study reveals that nuclear instability is a core feature of cancer, and links nuclear integrity, cell state, and immune signaling.

Effect of moxibustion on knee joint stiffness characteristics in recreational athletes pre- and post-fatigue.

Objective: Joint stiffness results from the coupling of the nervous system and joint mechanics, and thus stiffness is a comprehensive representation of joint stability. It has been reported that moxibustion can alleviate general weakness and fatigue symptoms and subsequently may influence joint stiffness. This study investigated whether moxibustion could enhance knee joint stiffness in recreational athletes pre- and post-fatigue. Methods: Eighteen participants were randomized into intervention (5 males: 20.6 ± 1.5 yr; 4 females: 20.8 ± 1.5 yr) and control groups (5 males: 19.4 ± 0.9 yr; 4 females: 20.5 ± 0.6 yr). The intervention group received indirect moxibustion applied to acupoints ST36 (bilateral) and CV4 for 30 min every other day for 4 consecutive weeks. The control group maintained regular exercise without moxibustion. Peak torque (PT) of right knee extensor, relaxed and contracted muscle stiffness (MS) of vastus lateralis, and knee extensor musculoarticular stiffness (MAS) was assessed with an isokinetic dynamometer (IsoMed 2000), myometer, and free oscillation technique, respectively. Measurements were taken at three time points: pre-intervention, post-intervention/pre-fatigue, and post-fatigue. Results: MAS (P = 0.006) and PT (P = 0.007) in the intervention group increased more from pre-to post-intervention compared with the control group. Post-fatigue MAS (P = 0.016) and PT (P = 0.031) increased more in the intervention group than in the control group. Conclusion: Moxibustion enhanced PT and knee MAS, suggesting that this intervention could be used in injury prevention and benefit fatigue resistance in young recreational athletes.

Gabapentin alleviated the cough hypersensitivity and neurogenic inflammation in a guinea pig model with repeated intra-esophageal acid perfusion.

OBJECTIVE: The anti-tussive effect of gabapentin and its underlying neuromodulatory mechanism were investigated via a modified guinea pig model of gastroesophageal reflux-related cough (GERC). METHODS: Intra-esophageal perfusion with hydrochloric acid (HCl) was performed every other day 12 times to establish the GERC model. High-dose gabapentin (48 mg/kg), low-dose gabapentin (8 mg/kg), or saline was orally administered for 2 weeks after modeling. Cough sensitivity, airway inflammation, lung and esophagus histology, levels of substance P (SP), and neurokinin-1 (NK1)-receptors were monitored. RESULTS: Repeated intra-esophageal acid perfusion aggravated the cough sensitivity in guinea pigs in a time-dependent manner. The number of cough events was significantly increased after 12 times HCl perfusion, and the hypersensitivity period was maintained for 2 weeks. The SP levels in BALF, trachea, lung, distal esophagus, and vagal ganglia were increased in guinea pigs receiving HCl perfusion. The intensity of cough hypersensitivity in the GERC model was significantly correlated with increased SP expression in the airways. Both high and low doses of gabapentin administration could reduce cough hypersensitivity exposed to HCl perfusion, attenuate airway inflammatory damage, and inhibit neurogenic inflammation by reducing SP expression from the airway and vagal ganglia. CONCLUSIONS: Gabapentin can desensitize the cough sensitivity in the GERC model of guinea pig. The anti-tussive effect is associated with the alleviated peripheral neurogenic inflammation as reflected in the decreased level of SP.

Dynamic range enhancement of self-referenced spectral interferometry with extended time excursion method by the cascaded Kerr lens process.

Self-referenced spectral interferometry with extended time excursion (SRSI-ETE) is a powerful method for single-shot characterization of the temporal contrast of a high peak power laser, which has high temporal resolution but a low dynamic range. Here, a temporal contrast reduction method is proposed that uses the cascaded Kerr lens process in two thin glass plates. Combined with the SRSI-ETE method, the measurement dynamic range of the method is increased about two orders of magnitude while having a 20 fs temporal resolution and a 40 ps time window in single shot.

Artificial intelligence-based refractive error prediction and EVO-implantable collamer lens power calculation for myopia correction.

BACKGROUND: Implantable collamer lens (ICL) has been widely accepted for its excellent visual outcomes for myopia correction. It is a new challenge in phakic IOL power calculation, especially for those with low and moderate myopia. This study aimed to establish a novel stacking machine learning (ML) model for predicting postoperative refraction errors and calculating EVO-ICL lens power. METHODS: We enrolled 2767 eyes of 1678 patients (age: 27.5 ± 6.33 years, 18-54 years) who underwent non-toric (NT)-ICL or toric-ICL (TICL) implantation during 2014 to 2021. The postoperative spherical equivalent (SE) and sphere were predicted using stacking ML models [support vector regression (SVR), LASSO, random forest, and XGBoost] and training based on ocular dimensional parameters from NT-ICL and TICL cases, respectively. The accuracy of the stacking ML models was compared with that of the modified vergence formula (MVF) based on the mean absolute error (MAE), median absolute error (MedAE), and percentages of eyes within ± 0.25, ± 0.50, and ± 0.75 diopters (D) and Bland-Altman analyses. In addition, the recommended spheric lens power was calculated with 0.25 D intervals and targeting emmetropia. RESULTS: After NT-ICL implantation, the random forest model demonstrated the lowest MAE (0.339 D) for predicting SE. Contrarily, the SVR model showed the lowest MAE (0.386 D) for predicting the sphere. After TICL implantation, the XGBoost model showed the lowest MAE for predicting both SE (0.325 D) and sphere (0.308 D). Compared with MVF, ML models had numerically lower values of standard deviation, MAE, and MedAE and comparable percentages of eyes within ± 0.25 D, ± 0.50 D, and ± 0.75 D prediction errors. The difference between MVF and ML models was larger in eyes with low-to-moderate myopia (preoperative SE > - 6.00 D). Our final optimal stacking ML models showed strong agreement between the predictive values of MVF by Bland-Altman plots. CONCLUSION: With various ocular dimensional parameters, ML models demonstrate comparable accuracy than existing MVF models and potential advantages in low-to-moderate myopia, and thus provide a novel nomogram for postoperative refractive error prediction and lens power calculation.

IGF2BP1-mediated N6-methyladenosine modification promotes intrahepatic cholangiocarcinoma progression.

N6-methyladenosine (m6A) RNA methylation and its associated RNA-binding protein insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1) are involved in tumor initiation and progression. Here, we explored the biological function and clinical significance of IGF2BP1 in intrahepatic cholangiocarcinoma (iCCA). We found that IGF2BP1 expression was upregulated by H3K27 acetylation enrichment of its promoter, which positively correlated with poor clinicopathological characteristics and survival. Gain- and loss-of-function experiments showed that IGF2BP1 overexpression (knockdown) enhanced (attenuated) iCCA growth and metastasis in vitro and in vivo. Mechanistically, IGF2BP1 not only regulated the c-Myc/p16 axis to promote iCCA growth and inhibit senescence, but also activated the ZIC2/PAK4/AKT/MMP2 axis to induce tumor metastasis. More importantly, BTYNB, a recently identified IGF2BP1 inhibitor, exerted promising anti-tumor efficacy in a patient-derived xenograft (PDX) model, and IGF2BP1 conditional knockout (cKO) reduced the tumor burden. These results demonstrate the crucial role of IGF2BP1 in iCCA progression via m6A-dependent modification, highlighting IGF2BP1 as a potential therapeutic target in iCCA.

Embracing enzyme promiscuity with activity-based compressed biosensing.

The development of protease-activatable drugs and diagnostics requires identifying substrates specific to individual proteases. However, this process becomes increasingly difficult as the number of target proteases increases because most substrates are promiscuously cleaved by multiple proteases. We introduce a method-substrate libraries for compressed sensing of enzymes (SLICE)-for selecting libraries of promiscuous substrates that classify protease mixtures (1) without deconvolution of compressed signals and (2) without highly specific substrates. SLICE ranks substrate libraries using a compression score (C), which quantifies substrate orthogonality and protease coverage. This metric is predictive of classification accuracy across 140 in silico (Pearson r = 0.71) and 55 in vitro libraries (r = 0.55). Using SLICE, we select a two-substrate library to classify 28 samples containing 11 enzymes in plasma (area under the receiver operating characteristic curve [AUROC] = 0.93). We envision that SLICE will enable the selection of libraries that capture information from hundreds of enzymes using fewer substrates for applications like activity-based sensors for imaging and diagnostics.