Estimation of soybean yield based on high-throughput phenotyping and machine learning.

Introduction: Soybeans are an important crop used for food, oil, and feed. However, China's soybean self-sufficiency is highly inadequate, with an annual import volume exceeding 80%. RGB cameras serve as powerful tools for estimating crop yield, and machine learning is a practical method based on various features, providing improved yield predictions. However, selecting different input parameters and models, specifically optimal features and model effects, significantly influences soybean yield prediction. Methods: This study used an RGB camera to capture soybean canopy images from both the side and top perspectives during the R6 stage (pod filling stage) for 240 soybean varieties (a natural population formed by four provinces in China: Sichuan, Yunnan, Chongqing, and Guizhou). From these images, the morphological, color, and textural features of the soybeans were extracted. Subsequently, feature selection was performed on the image parameters using a Pearson correlation coefficient threshold ≥0.5. Five machine learning methods, namely, CatBoost, LightGBM, RF, GBDT, and MLP, were employed to establish soybean yield estimation models based on the individual and combined image parameters from the two perspectives extracted from RGB images. Results: (1) GBDT is the optimal model for predicting soybean yield, with a test set R2 value of 0.82, an RMSE of 1.99 g/plant, and an MAE of 3.12%. (2) The fusion of multiangle and multitype indicators is conducive to improving soybean yield prediction accuracy. Conclusion: Therefore, this combination of parameters extracted from RGB images via machine learning has great potential for estimating soybean yield, providing a theoretical basis and technical support for accelerating the soybean breeding process.

Efficacy and Safety of Snap Needles in the Treatment of Postoperative Hemorrhoidal Pain: A Systematic Review and Meta-Analysis.

Purpose: The aim of this study is to evaluate the efficacy and safety of Snap Needles (SN) in the management of Postoperative Hemorrhoidal Pain (POHP). Patients and Methods: A systematic search was conducted in various databases, including EMBASE, Web of Science, PubMed, WanFang database, China National Knowledge Infrastructure (CNKI), China Biomedical Literature Database (CBM), and China Science and Technology Journal Database (VIP), spanning from their inception to August 2023, to identify relevant randomized controlled trials (RCTs) on SN for POHP. The primary outcome measure was the Visual Analog Scale (VAS), while secondary outcomes encompassed the Total Effective Rate (TER), Wound Healing Time (WHT), Pain Relief Time (PRT), Pain Disappearance Time (PDT), and Adverse Events (AEs). The Cochrane Risk of Bias Tool was employed to assess the quality of individual studies. A meta-analysis was conducted using RevMan 5.4.1 software. Results: The meta-analysis included 11 RCTs involving 1188 POHP patients, with an overall assessment of study quality ranging from very low to moderate. The findings revealed that the SN group exhibited significant improvements in treatment outcomes when compared to the control group (CG). These improvements were reflected in reduced VAS scores (mean difference [MD] = -1.10, 95% confidence interval [CI]: -1.31, -0.89, P < 0.05), shorter WHT (MD = -2.55, 95% CI: -3.02, -2.09, P < 0.05), quicker PRT (MD = -7.99, 95% CI: -8.48, -7.49, P < 0.05), fewer AEs (risk ratio [RR] = 0.38, 95% CI: 0.22, 0.67, P < 0.05), improved TER (RR = 1.18, 95% CI: 1.09, 1.27, P < 0.05), and faster PDT (MD = 19.24, 95% CI: 14.17, 24.31, P < 0.05). Conclusion: The use of SN appears to yield favorable outcomes in the treatment of POHP, and is potentially an alternative therapy to western drug therapy.

Sub-micron pixel polarization-sensitive photodetector based on silicon nanowire.

Silicon nanowire is a potential candidate to be used as polarization-sensitive material, but the relative mechanism of polarization response must be carried out. Herein, a sub-micron metal-single silicon nanowire-metal photodetector exhibits polarization-sensitive characteristics with an anisotropic photocurrent ratio of 1.59 at 780 nm, an excellent responsivity of 24.58 mA/W, and a high detectivity of 8.88 × 109 Jones at 980 nm. The underlying principle of optical anisotropy in silicon nanowire is attributed to resonance enhancement verified by polarizing light microscopy and simulation. Furthermore, Stokes parameter measurements and imaging are all demonstrated by detecting the characteristics of linearly polarized light and imaging the polarizer array, respectively. Given the maturity of silicon processing, the sub-micron linearly polarized light detection proposed in this study lays the groundwork for achieving highly integrated, simplified processes, and cost-effective on-chip polarization-sensitive optical chips in the future.

Enhanced Complement Expression in the Tumor Microenvironment Following Neoadjuvant Therapy: Implications for Immunomodulation and Survival in Pancreatic Ductal Adenocarcinoma.

Background: Neoadjuvant therapy (NAT) is increasingly being used for pancreatic ductal adenocarcinoma (PDAC) treatment. However, its specific effects on carcinoma cells and the tumor microenvironment (TME) are not fully understood. This study aims to investigate how NAT differentially impacts PDAC's carcinoma cells and TME. Methods: Spatial transcriptomics was used to compare gene expression profiles in carcinoma cells and the TME between 23 NAT-treated and 13 NAT-naïve PDAC patients, correlating with their clinicopathologic features. Analysis of an online single-nucleus RNA sequencing (snRNA-seq) dataset was performed for validation of the specific cell types responsible for NAT-induced gene expression alterations. Results: NAT not only induces apoptosis and inhibits proliferation in carcinoma cells but also significantly remodels the TME. Notably, NAT induces a coordinated upregulation of multiple key complement genes (C3, C1S, C1R, C4B and C7) in the TME, making the complement pathway one of the most significantly affected pathways by NAT. Patients with higher TME complement expression following NAT exhibit improved overall survival. These patients also exhibit increased immunomodulatory and neurotrophic cancer-associated fibroblasts (CAFs); more CD4+ T cells, monocytes, and mast cells; and reduced immune exhaustion gene expression. snRNA-seq analysis demonstrates C3 complement was specifically upregulated in CAFs but not in other stroma cell types. Conclusions: NAT can enhance complement production and signaling within the TME, which is associated with reduced immunosuppression in PDAC. These findings suggest that local complement dynamics could serve as a novel biomarker for prognosis, evaluating treatment response and resistance, and guiding therapeutic strategies in NAT-treated PDAC patients.

Salinity decreases methane concentrations in Chinese lakes.

Lakes are important sources of methane (CH4), and understanding the influence of environmental factors on CH4 concentration in lake water is crucial for accurately assessing CH4 emission from lakes. In this study, we investigated CH4 concentration in two connected Tibetan Plateau lakes, Lake Keluke (an open freshwater lake) and Lake Tuosu (a closed saline lake), through in-situ continuous measurements taken in different months from 2021 to 2023. The results show substantial spatial and seasonal variations in CH4 concentrations in the two lakes, while the CH4 concentrations in Lake Keluke are consistently higher than those in Lake Tuosu for each month. Despite sharing similar environmental conditions due to connected (e.g. pH, water temperature, dissolved oxygen content, and total organic carbon content), the critical difference between the two lakes is their salinity. This implies that salinity is the critical factor contributing to the decrease in CH4 concentrations in Lake Tuosu, possibly due to the changes in microbial species between freshwater and brackish/saline lakes. Additionally, to further validate the effect of salinity on CH4 concentrations in lake water, we compared the CH4 concentrations of 33 lakes (including 5 saline lakes and 28 freshwater lakes) from the Tibetan Plateau, Chinese Loess Plateau, and Yangtze Plain, and found that saline lakes consistently exhibit lower CH4 concentrations (avg. 0.08 µmol/L), while freshwater lakes generally display higher CH4 concentrations (avg. 1.25 µmol/L) with considerable fluctuations. Consequently, freshwater and saline lakes exhibit distinct CH4 emissions, which could be used for more accurate estimation of global CH4 emission from lakes.

On-Site Quantitative Visualization of Singlet Oxygen in Crops via an Organic Small Molecule-Based Ratiometric Fluorescent Probe and a Mobile Fluorescence Analysis Device.

Singlet oxygen (1O2) plays imperative roles in a variety of biotic or abiotic stresses in crops. The change of its concentration within a crop is closely related to the crop growth and development. Accordingly, there is an urgent need to develop an efficient analytical method for on-site quantitative detection of 1O2 in crops. Here, we judiciously constructed a novel ratiometric fluorescent probe, SX-2, for the detection of 1O2 in crops. Upon treating with 1O2, probe SX-2 displayed highly selective ratiometric fluorescence response, which is favorable for the quantitative detection of 1O2. Concurrently, the fluorescence solution color of probe SX-2 was varied, obviously from blue to yellow, indicating that the probe is beneficial for on-site detection by the naked eye. Sensing reaction mechanism studies showed that the 2,3-diphenyl imidazole group in SX-2 could function as a new selective recognition group for 1O2. Probe SX-2 was utilized for the detection of photoirradiation-induced 1O2 and endogenous 1O2 in living cells. The changes in the 1O2 level in zebrafish were also tracked by fluorescence imaging. In addition, the production of 1O2 in crop leaves under a light source of different wavelengths was studied. The results demonstrated more 1O2 were produced under a light source of 365 nm. Furthermore, to achieve on-site quantitative detection, a mobile fluorescence analysis device has been made. Probe SX-2 and mobile fluorescence analysis device were capable of on-site quantitative detecting of 1O2 in crops. The method developed herein will be convenient for the on-site quantitative measurement of 1O2 in distinct crops.

Machine Learning to Promote Efficient Screening of Low-Contact Electrode for 2D Semiconductor Transistor Under Limited Data.

Low-barrier and high-injection electrodes are crucial for high-performance (HP) 2D semiconductor devices. Conventional trial-and-error methodologies for electrode material screening are impractical because of their low efficiency and arbitrary specificity. Although machine learning has emerged as a promising alternative to tackle this problem, its practical application in semiconductor devices is hindered by its substantial data requirements. In this paper, a comprehensive scheme combining an autoencoding regularized adversarial neural network and a feature-adaptive variational active learning algorithm for screening low-contact electrode materials for 2D semiconductor transistors with limited data is proposed. The proposed scheme exhibits exceptional performance by training with only 15% of the total data points, where the mean square errors are 0.17 and 0.27 eV for the vertical and lateral Schottky barrier, respectively, and 2.88% for tunneling probability. Further, it exhibits an optimal predictive performance for 100 randomly sampled training datasets, reveals the underlying physical insight based on the identified features, and realizes continual improvement by employing detailed density-of-states descriptors. Finally, the empirical evaluations of the transport characteristics are conducted and verified by constructing MOSFET devices. These findings demonstrate the considerable potential of machine-learning techniques for screening high-efficiency electrode materials and constructing HP 2D semiconductor devices.

The vasculogenic mimicry related signature predicts the prognosis and immunotherapy response in renal clear cell carcinoma.

BACKGROUND: Clear cell carcinoma of the kidney is a common urological malignancy characterized by poor patient prognosis and treatment outcomes. Modulation of vasculogenic mimicry in tumor cells alters the tumor microenvironment and the influx of tumor-infiltrating lymphocytes, and the combination of its inducers and immune checkpoint inhibitors plays a synergistic role in enhancing antitumor effects. METHODS: We downloaded the data from renal clear cell carcinoma samples and vasculogenic mimicry-related genes to establish a new vasculogenic mimicry-related index (VMRI) using a machine learning approach. Based on VMRI, patients with renal clear cell carcinoma were divided into high VMRI and low VMRI groups, and patients' prognosis, clinical features, tumor immune microenvironment, chemotherapeutic response, and immunotherapeutic response were systematically analyzed. Finally, the function of CDH5 was explored in renal clear cell carcinoma cells. RESULTS: VMRI can be used for prognostic and immunotherapy efficacy prediction in a variety of cancers, which consists of four vasculogenic mimicry-related genes (CDH5, MMP9, MAPK1, and MMP13), is a reliable predictor of survival and grade in patients with clear cell carcinoma of the kidney and has been validated in multiple external datasets. We found that the high VMRI group presented higher levels of immune cell infiltration, which was validated by pathological sections. We performed molecular docking prediction of vasculogenic mimicry core target proteins and identified natural small molecule drugs with the highest affinity for the target protein. Knockdown of CDH5 inhibited the proliferation and migration of renal clear cell carcinoma. CONCLUSIONS: The VMRI identified in this study allows for accurate prognosis assessment of patients with renal clear cell carcinoma and identification of patient populations that will benefit from immunotherapy, providing valuable insights for future precision treatment of patients with renal clear cell carcinoma.

All-dielectric high-NA achromatic metalenses in the mid-infrared band based on subregions.

For conventional refractive lenses, chromatic aberration inevitably occurs due to the refractive index variation of the lens material with the incident wavelength, leading to axial aberrations and lower imaging system quality. Achromatic metalenses have demonstrated a great capability to solve this problem and been extensively investigated. However, the metalens achromatic method involves construction of a unit structure satisfying a phase distribution greater than 0-2π or phase compensation. Although this design method can obtain a good achromatic effect, finding a unit that satisfies a linear distribution during design is difficult. In this paper, we use subregion discrete wavelength modulation to achieve broadband achromatism. The total number of structural units in each region is optimized for different incident wavelengths, and the internal and external ring unit structures are also optimized. This achromatic metalens exhibits a large aperture and a high numerical aperture in the 4.2-4.7 µm mid-infrared band (NA = 0.83). Our research has strong potential and application prospects in ultracompact imaging and laser beam shaping.

Maximizing carbon sequestration potential in Chinese forests through optimal management.

Forest carbon sequestration capacity in China remains uncertain due to underrepresented tree demographic dynamics and overlooked of harvest impacts. In this study, we employ a process-based biogeochemical model to make projections by using national forest inventories, covering approximately 415,000 permanent plots, revealing an expansion in biomass carbon stock by 13.6 ± 1.5 Pg C from 2020 to 2100, with additional sink through augmentation of wood product pool (0.6-2.0 Pg C) and spatiotemporal optimization of forest management (2.3 ± 0.03 Pg C). We find that statistical model might cause large bias in long-term projection due to underrepresentation or neglect of wood harvest and forest demographic changes. Remarkably, disregarding the repercussions of harvesting on forest age can result in a premature shift in the timing of the carbon sink peak by 1-3 decades. Our findings emphasize the pressing necessity for the swift implementation of optimal forest management strategies for carbon sequestration enhancement.

Consistent abnormal activity in the putamen by dopamine modulation in Parkinson's disease: A resting-state neuroimaging meta-analysis.

OBJECTIVE: This study aimed to elucidate brain areas mediated by oral anti-parkinsonian medicine that consistently show abnormal resting-state activation in PD and to reveal their functional connectivity profiles using meta-analytic approaches. METHODS: Searches of the PubMed, Web of Science databases identified 78 neuroimaging studies including PD OFF state (PD-OFF) versus (vs.) PD ON state (PD-ON) or PD-ON versus healthy controls (HCs) or PD-OFF versus HCs data. Coordinate-based meta-analysis and functional meta-analytic connectivity modeling (MACM) were performed using the activation likelihood estimation algorithm. RESULTS: Brain activation in PD-OFF vs. PD-ON was significantly changed in the right putamen and left inferior parietal lobule (IPL). Contrast analysis indicated that PD-OFF vs. HCs had more consistent activation in the right paracentral lobule, right middle frontal gyrus, right thalamus, left superior parietal lobule and right putamen, whereas PD-ON vs. HCs elicited more consistent activation in the bilateral middle temporal gyrus, left occipital gyrus, right inferior frontal gyrus and right caudate. MACM revealed coactivation of the right putamen in the direct contrast of PD-OFF vs. PD-ON. Subtraction analysis of significant coactivation clusters for PD-OFF vs. PD-ON with the medium of HCs showed effects in the sensorimotor, top-down control, and visual networks. By overlapping the MACM maps of the two analytical strategies, we demonstrated that the coactivated brain region focused on the right putamen. CONCLUSIONS: The convergence of local brain regions and co-activation neural networks are involved the putamen, suggesting its potential as a specific imaging biomarker to monitor treatment efficacy. SYSTEMATIC REVIEW REGISTRATION: [https://www.crd.york.ac.uk/PROSPERO/], identifier [CRD CRD42022304150].

Correlation between the MNCD classification-based staging of Parkinson's disease and quality of life: a cross-sectional study.

Parkinson's disease (PD) is a highly heterogeneous neurodegenerative disorder with varying clinical subtypes. Recently, a novel classification called MNCD (Motor/Non-motor/Cognition/Dependency) has been proposed, which can also include staging based on disease severity. We aim to investigate which staging, the MNCD classification and staging or Hoehn and Yahr (H&Y) staging, exhibits a stronger correlation with the 39-item Parkinson's Disease Questionnaire (PDQ-39). In a cross-sectional study conducted at our single center, 357 PD patients were recruited. Data encompassed scores from various assessments such as the Movement Disorder Society of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Parts I, II, III and IV, Montreal Cognitive Assessment (MoCA), PDQ-39, and the H&Y scale. The mean age of these patients was 66.4 ± 9.1 years old, and the majority (54.6%) were male. MNCD stages: stage 1 (N = 3, 0.8%), stage 2 (N = 62, 17.4%), stage 3 (N = 187, 52.4%), stage 4 (N = 86, 24.1%), and stage 5 (N = 19, 5.3%). The top 5 most frequent PD-related clinical symptoms were sleep disturbances (89.6%), fatigue (69.7%), mild cognitive impairment (68.9%), constipation (65.8%), and postural instability (65.5%). The PDQ-39 demonstrated a positive correlation with both MNCD staging and H&Y staging. Moreover, the MNCD staging exhibited a stronger correlation with PDQ-39 compared to H&Y staging. The correlation between the MNCD classification and staging with the quality of life in PD patients is more statistically significant compared to the H&Y staging.

Morphometric similarity differences in drug-naive Parkinson's disease correlate with transcriptomic signatures.

BACKGROUND: Differences in cortical morphology have been reported in individuals with Parkinson's disease (PD). However, the pathophysiological mechanism of transcriptomic vulnerability in local brain regions remains unclear. OBJECTIVE: This study aimed to characterize the morphometric changes of brain regions in early drug-naive PD patients and uncover the brain-wide gene expression correlates. METHODS: The morphometric similarity (MS) network analysis was used to quantify the interregional structural similarity from multiple magnetic resonance imaging anatomical indices measured in each brain region of 170 early drug-naive PD patients and 123 controls. Then, we applied partial least squares regression to determine the relationship between regional changes in MS and spatial transcriptional signatures from the Allen Human Brain Atlas dataset, and identified the specific genes related to MS differences in PD. We further investigated the biological processes by which the PD-related genes were enriched and the cellular characterization of these genes. RESULTS: Our results showed that MS was mainly decreased in cingulate, frontal, and temporal cortical areas and increased in parietal and occipital cortical areas in early drug-naive PD patients. In addition, genes whose expression patterns were associated with regional MS changes in PD were involved in astrocytes, excitatory, and inhibitory neurons and were functionally enriched in neuron-specific biological processes related to trans-synaptic signaling and nervous system development. CONCLUSIONS: These findings advance our understanding of the microscale genetic and cellular mechanisms driving macroscale morphological abnormalities in early drug-naive PD patients and provide potential targets for future therapeutic trials.

Combined transcriptomics and metabolomics to analyse the response of Cuminum cyminum L. under Pb stress.

Lead (Pb) can disrupt plant gene expression, modify metabolite contents, and influence the growth of plants. Cuminum cyminum L. is highly adaptable to adversity, but molecular mechanism by which it responds to Pb stress is unknown. For this study, transcriptomic and metabolomic sequencing was performed on root tissues of C. cyminum under Pb stress. Our results showed that high Pb stress increased the activity of peroxidase (POD), the contents of malondialdehyde (MDA) and proline by 80.03 %, 174.46 % and 71.24 %, respectively. Meanwhile, Pb stress decreased the activities of superoxide dismutase (SOD) and catalase (CAT) as well as contents of soluble sugars and GSH, which thus affected the growth of C. cyminum. In addition, Pb stress influenced the accumulation and transport of Pb in C. cyminum. Metabolomic results showed that Pb stress affected eight metabolic pathways involving 108 differentially expressed metabolites, primarily amino acids, organic acids, and carbohydrates. The differentially expressed genes identified through transcriptome analysis were mainly involved the oxidation reductase activity, transmembrane transport, phytohormone signaling, and MAPK signaling pathway. The results of this study will help to understand the molecular mechanisms of C. cyminum response to Pb stress, and provide a basis for screening seeds with strong resistance to heavy metals.

Spatial patterns of Holocene temperature changes over mid-latitude Eurasia.

The Holocene temperature conundrum, the discrepancy between proxy-based Holocene global cooling and simulated global annual warming trends, remains controversial. Meanwhile, reconstructions and simulations show inconsistent spatial patterns of terrestrial temperature changes. Here we report Holocene alkenone records to address spatial patterns over mid-latitude Eurasia. In contrast with long-term cooling trends in warm season temperatures in northeastern China, records from southwestern Siberia are characterized by colder conditions before ~6,000 years ago, thus long-term warming trends. Together with existing records from surrounding regions, we infer that colder airmass might have prevailed in the interior of mid-latitude Eurasian continent during the early to mid-Holocene, perhaps associated with atmospheric response to remnant ice sheets. Our results challenge the proposed seasonality bias in proxies and modeled spatial patterns in study region, highlighting that spatial patterns of Holocene temperature changes should be re-considered in record integrations and model simulations, with important implications for terrestrial hydroclimate changes.

PIF4 interacts with ABI4 to serve as a transcriptional activator complex to promote seed dormancy by enhancing ABA biosynthesis and signaling.

Transcriptional regulation plays a key role in the control of seed dormancy, and many transcription factors (TFs) have been documented. However, the mechanisms underlying the interactions between different TFs within a transcriptional complex regulating seed dormancy remain largely unknown. Here, we showed that TF PHYTOCHROME-INTERACTING FACTOR4 (PIF4) physically interacted with the abscisic acid (ABA) signaling responsive TF ABSCISIC ACID INSENSITIVE4 (ABI4) to act as a transcriptional complex to promote ABA biosynthesis and signaling, finally deepening primary seed dormancy. Both pif4 and abi4 single mutants exhibited a decreased primary seed dormancy phenotype, with a synergistic effect in the pif4/abi4 double mutant. PIF4 binds to ABI4 to form a heterodimer, and ABI4 stabilizes PIF4 at the protein level, whereas PIF4 does not affect the protein stabilization of ABI4. Subsequently, both TFs independently and synergistically promoted the expression of ABI4 and NCED6, a key gene for ABA anabolism. The genetic evidence is also consistent with the phenotypic, physiological and biochemical analysis results. Altogether, this study revealed a transcriptional regulatory cascade in which the PIF4-ABI4 transcriptional activator complex synergistically enhanced seed dormancy by facilitating ABA biosynthesis and signaling.

The global, regional, and national disease burden of breast cancer attributable to tobacco from 1990 to 2019: a global burden of disease study.

OBJECTIVE: Tobacco has been identified as a significant contributory element to the development of breast cancer. Our objective was to evaluate the spatiotemporal trends of tobacco-related breast cancer at the global, regional, and national scales during 1990-2019. METHODS: We extracted data on mortality, disability adjusted of life years (DALYs), age-standardized mortality rate (ASMR), and age-standardized DALYs rate (ASDR) from the Global Burden of Disease (GBD) study 2019. Estimated annual percentage change (EAPC) was computed to assess the temporal change in ASDR and ASMR. RESULTS: In 2019, the deaths and DALYs attributed to tobacco-related breast cancer were estimated to be 35,439 (95% UI: 22,179-48,119) and 1,060,590 (95% UI: 622,550-1,462,580), respectively. These figures accounted for 5.1% and 5.2% of the total burden of breast cancer. ASMR and ASDR increased in low SDI regions, remained stable in low-middle and middle SDI regions and declined in high and high-middle SDI regions. The burden of breast cancer attributable to tobacco varied notably among regions and nations. Oceania, Southern Latin America, and Central Europe were the GBD regions with the highest number of ASMR and DALYs. There was a positive relationship between age-standardized rate and SDI value in 2019 across 204 nations or territories. A negative association was observed between the EAPC in ASMR or ASDR and the human development index (HDI) in 2019 (R = -0.55, p < 0.01 for ASMR; R = -0.56, p < 0.01 for ASDR). CONCLUSION: Tobacco is one important and modifiable risk factor for breast cancer. The heterogeneity in both the spatial and temporal distribution can be attributed to factors such as aging, population growth, and SDI. These findings substantiate the necessity of expediting the enforcement of tobacco-free legislation in order to safeguard populations from the detrimental effects of tobacco.

Biomechanical characterization of firefighters running under different rescue tasks.

The biomechanical characteristics of runs in firefighters with different rescue tasks are unclear. This study aimed to explore the biomechanical characteristics of firefighters running in different rescue tasks and provide theoretical and practical references for firefighter training and occupational injury prevention. Eighteen professional healthy male firefighters were randomly selected as participants and tested running on different rescue tasks: wearing firefighting protective clothing (FPC), FPC+carrying a gas can (20 kg, FPC+ C), and FPC+carrying a mannequin (60 kg, FPC+M). Eight Qualisys infrared cameras and an AMTI 3D force measurement platform were used for the participant's acquisition of lower limb kinematic/kinetic data. The results showed that gait velocity and stride length of the FPC+GC and FPC+ M rescue tasks were significantly decreased compared to the FPC rescue task, while the support time was significantly increased. Compared to the FPC rescue task, the FPC+GC rescue task showed significant decreases in vertical ground reaction force (vGRF), minimum ankle dorsiflexion angle, and the maximum ankle plantarflexion power. In contrast, the FPC+M rescue task demonstrated significant increases in ankle range of motion, maximum hip extension angle, minimum knee flexion angle, maximum ankle dorsiflexion angle, maximum hip extension moment, maximum knee flexion moment, maximum hip flexion power, and hip and knee stiffness while exhibiting significant decreases in minimum ankle dorsiflexion angle. Compared to the FPC+ GC rescue task, the FPC+M rescue task exhibited significant increases in the maximum hip extension angle, minimum knee flexion angle, maximum ankle dorsiflexion angle, maximum hip flexion moment, maximum hip extension moment, maximum knee flexion moment, maximum ankle plantarflexion moment, maximum hip flexion power, maximum ankle dorsiflexion power, hip stiffness, and vGRF. Conversely, it showed significant decreases in the maximum knee flexion power. In conclusion, compared to the FPC rescue task, the FPC+GC and FPC+M rescue tasks altered the firefighter's gait performance, as evidenced by decreased gait velocity and stride length and increased support time. FPC+M rescue task would increase firefighter's risk of hip and knee injuries. Therefore, we suggest firefighters increase their strength training of the trunk, hip, and knee joint muscles as part of their daily training programs under large weight load status (60 kg and above) to reduce injury risk during rescue tasks.

Clinical effects and biological mechanisms of exercise on lumbar disc herniation.

Lumbar Disc Herniation (LDH) is a syndrome in which lumbar disc degeneration, rupture of the annulus fibrosus, and herniation of the nucleus pulposus irritate and compress the nerve roots and cauda equina, resulting in the main manifestations of lumbar pain and/or lower extremity pain. There is evidence in various clinical areas that exercise is effective in treating LDH, and exercise intervention for more than 2 weeks reduces disease activity in LDH. However, the mechanism of exercise's action in reducing disease activity in LDH is unclear. In this article, we first summarize and highlight the effectiveness of exercise in treating LDH and provide guideline recommendations regarding exercise type, intensity, frequency, and duration. Then, we integrate the existing evidence and propose biological mechanisms for the potential effects of exercise on neuromechanical compression, inflammatory chemical stimuli, and autoimmune responses from the perspective of LDH pathogenesis as an entry point. However, a large body of evidence was obtained from non-LDH populations. Future research needs to investigate further the proposed biological mechanisms of exercise in reducing disease activity in LDH populations. This knowledge will contribute to the basic science and strengthen the scientific basis for prescribing exercise therapy for the routine clinical treatment of LDH.