Platelets play a crucial role in cancer blood metastasis. Various cancer-related factors such as Toll-like receptors (TLRs), adenosine diphosphate (ADP) or extracellular matrix (ECM) can activate these small particles that function in hemostasis and thrombosis. Moreover, platelets induce Epithelial Mesenchymal Transition (EMT) to promote cancer progression and invasiveness. The activated platelets protect circulating tumor cells from immune surveillance and anoikis. They also mediate tumor cell arrest, extravasation and angiogenesis in distant organs through direct or indirect modulation, creating a metastatic microenvironment. This review summarizes the recent advances and progress of mechanisms in platelet activation and its interaction with cancer cells in metastasis. Cancer metastasis is the cause of a huge proportion (around 90%) of cancer-related deaths, and curing metastatic diseases remains a challenge despite great progress in diagnosis of cancer. Many cancer types metastasize through the circulatory system. Metastasis begins when cancer cells in the primary tumor, enabled by processes such as the Epithelial Mesenchymal Transition (EMT), gain invasion power and spread to distant sites . Cancer Platelets are tiny anucleate cells that originate from megakaryocytes, and the process of platelet production takes place predominantly in the bone marrow. During platelet generation, long extensions of megakaryocytes called proplatelets grow into the vasculature and are broken off by blood forces. Proplatelets in the blood are further divided into smaller platelets in the circulatory system . TraditiAs early as in 1865, Armand Trousseau has documented the development of venous thrombosis during the progress of pancreatic cancer, suggesting an interplay between cancer development and platelet activity and blood clot formation . Since tThere is numerous evidence of tumor cells inducing platelet activation and aggregation. Activating platelets and forming a complex with them allow CTCs to harness the benefits of platelet’s promotion of tumor growth and metastasis. Activated platelets become adhesive and cluster around CTCs, protecting them against shear stress and attack from immune cells. Platelet interaction also allows CTCs to better adhere to vascular endothelium at the metastatic site. Activated platelets can also secrete a plethora of growth factors such as transforming growth factor beta (TGFβ), vascular endothelial growth factor (VEGF), and platelet-derived growth factor (PDGF) that promote pro-metastatic processes such as epithelial–mesenchymal transition (EMT) and angiogenesis.Tumor cells can induce platelet activation and aggregation directly, either through release of soluble platelet agonists into the bloodstream or through contact between tumor cell and platelets. Tumor cells can release classic soluble factors such as adenosine diphosphate (ADP) . The traTumor cells can also indirectly activate and aggregate platelets through inducing pathways or formations of molecules that can lead to platelet activation. A common theme in many tumor cells’ mechanisms to activate platelets is releasing or inducing the expression of classic platelet agonists involved in the hemostasis or coagulation pathway. The tight association between platelet aggregating activity (PAA) and procoagulant activity (PCA) of tumor cells has been proposed in the twentieth century. PCA refers to the ability to convert prothrombin into the platelet agonist thrombin, which is a critical step in the blood coagulation pathway. As thrombin inhibitors can inhibit tumor cell-induced platelet aggregation by many tumor cell types, it is hypothesized that one-way tumor cells activate platelets is through activating coagulant factors, which eventually lead to the generation of thrombin. From rodent tumor cells, the protein with both PAA and PCA has been isolated. The component is termed cancer procoagulant (CP), and its activity is dependent on coagulant factor X but not VII. CP of tumor cells is thus proposed to be a factor X activator . As coagTumor cells can also activate platelets indirectly via innate immune cells in circulation. Shao et al. have discovered that carcinoma mucins can bind to both P-selectins on platelets and L-selectins on neutrophils, bringing the two cell types close to each other. Through interaction with mucins as well as bidirectional signaling between platelets and neutrophils via P-selectin and P-selectin glycoprotein ligand-1 (PSGL-1), both platelets and neutrophils are activated. Eventually, cathepsin G is released from neutrophils, further inducing platelet activation and aggregation through protease-activated receptor-4 (PAR4) . MoreoveDuring cancer metastasis, some cancer cells in the primary tumor gain invasion power, leave the primary tumor tissue, migrate into nearby stroma, and eventually intravasate into the blood or lymphatic system . PlateleEMT in cancer cells can be induced by a plethora of signals including transforming growth factor β (TGFβ), which are stored and secreted by platelets. TGFβ secreted by platelets can induce EMT and subsequent metastasis in breast, colon carcinoma and ovarian cancer cells , 24. KnoThe location of where platelets promote EMT of tumor cells has also been studied, and it has been shown that platelets can induce EMT in both primary tumor cells and CTCs. It has been well established that platelets are capable of intravasating into tumors, and extravascular platelets have been imaged in the tumor microenvironment of many tumor cells . In the Tumor metastasis is a highly inefficient process, as most of the tumor cells in circulation die quickly after extravasation. Circulating tumor cells face many stressors, including programmed cell death (termed anoikis) upon detachment from the extracellular matrix, blood shear forces and attack from the immune system . As a reBesides acting as a physical barrier between CTCs and NK cells, several other mechanisms of platelets preventing NK cell recognition and attack have been proposed. NK cells are activated through detecting either “missing self” or “induced self”. “Missing self” refers to low or absent expression of MHC class I protein whereas “induced self” refers to expression of ligands that can activate NK cell receptors such as natural killer group 2, member D (NKG2D) , 33. Pla2O2), yet a greater neutrophil-to-lymphocyte ratio (NLR) correlates with the number of CTCs as well as metastasis of pancreatic ductal adenocarcinoma after surgery and poorer survival of primary breast cancer patients [2O2, some CTCs can develop resistance to neutrophil cytotoxicity and form clusters with neutrophils. The inflammatory interaction between CTCs and neutrophils promotes proliferation and dissemination of tumor cells. Neutrophils are also capable of infiltrating primary tumors, and primary tumors with mutations that grant resistance to neutrophil killing will shed more CTC-neutrophil clusters [Besides NK cells, other immune cells can also interact with CTCs and influence the success of metastasis seeding, and platelets can regulate some of the interactions as well. Neutrophils can kill tumor cells through the production of hydrogen peroxide , immunoglobulin superfamily proteins (PECAM-1), C-type lectin receptor family proteins , leucine-rich glycoproteins (GPIb-IX-V), etc. These molecules are capable of bridging connections between platelets and vascular wall, tumor cells, and other platelets , 27, 45.Normally, platelets would only adhere to the endothelial wall when vascular injury occurred and materials in the extracellular matrix are exposed to blood elements. To enhance CTC binding to the vascular wall that are not experiencing significant damage, endothelial cells at the premetastatic site may be activated. Activation of endothelial cells can lead to their expression of adhesion molecules including E-selectin, P-selectin, vascular cell adhesion molecule (VCAM)-1 and intercellular adhesion molecule (ICAM)-1, all of which can facilitate tumor cell binding. Primary tumors can release soluble factors that induce activation of the endothelial cells at the metastatic site . BesidesAfter CTCs have stably adhered to the endothelium at metastatic site, platelets continue to facilitate the metastatic process, promoting transendothelial migration, invasion, and subsequent survival and proliferation of tumor cells. In an in vivo study, Weber showed that in thrombocytopenic mice, intravenously injected tumor cells mostly failed to extravasate after three days while most of tumor cells discovered in wild type mice had exited the vasculature. Moreover, activating integrin αVβ3 on tumor cells, which are crucial for promoting interaction with platelets, led to more efficient transendothelial migration in vitro . These rPlatelets can also enhance the invasive ability of tumor cells through the extracellular matrix, and this is typically evaluated by measuring cell movement through the Matrigel layer in vitro. Pang’s team discovered that after stimulating mammary adenocarcinoma cells with activated platelet membranes and growing them on Matrigel, the degradation of Matrigel was enhanced. Platelet-tumor cell binding is necessary for this process as inhibiting both P-selectin and integrin αIIbβ3 abrogated platelet binding and tumor cells’ ability to degrade the ECM . Interes2O2. Upon further inspection, G-CSF secretion may be responsible for neutrophil sequestration, but it is not sufficient to induce TEN cytotoxicity. CCL2 and CCL5 secreted by premetastatic lungs could be responsible for the entrainment of neutrophils [Platelet and leukocyte interplay also strongly influence the success of seeding metastasis. It is believed that leukocytes generally have positive effects on promoting tumor cell survival at the metastatic site, and recruitment of white blood cells are correlated with metastasis. Studies showed that leukocytes usually exert their effects during early stages of metastasis, influencing the formation of new metastatic foci. For instance, while initial seeding of tumor cells (around 2 h after tumor cell injection) were unaffected, metastasis events were reduced during the first 48 h of intravenous colon carcinoma cell injection in mouse models with depleted granulocytes . Similartrophils . Labelletrophils .Several studies have focused on the effect of platelet-leukocyte interplay on tumor cell extravasation and survival. Platelets and granulocytes together form the premetastatic niche for injected colon carcinoma cells. In in vivo models of tumor metastasis, injected tumor cells are immediately coated by platelets, and activated platelets subsequently release chemokines CXCL5 and CXCL7, which are chemokines attracting granulocytes . Many otRapidly growing and dividing malignant cells demand plenty of nutrients and oxygen. As a result, angiogenesis, the formation of new blood vessels, is pivotal for cancer progression. It is required for tumors to break out of dormancy . PlateleSince platelets contain both pro-angiogenic and anti-angiogenic molecules, the mechanisms by which platelets regulate the release of these counteracting signaling molecules has been an area of active research. The specificity of signaling molecules and receptors seem to play a huge role on platelet’s effect on angiogenesis. Previous studies suggest that stimulation of PAR1 on platelet surfaces leads to release of pro-angiogenic molecules like VEGF and inhibits secretion of anti-angiogenic molecules like endostatin, while stimulation of PAR4 induces secretion endostatin and inhibits VEGF release . InteresPlatelet-derived extracellular vesicles (PEV) can also induce angiogenesis upon transfer into vascular endothelial cells . StimulaGiven increasing evidence for platelets’ promotion of cancer metastasis, platelets are becoming increasingly popular as targets for preventing or attenuating metastasis. The effect of the classic AP drug aspirin has been a research hotspot, and multiple clinical and in vivo studies have supported its role in reducing metastasis in a wide range of cancer types. In a in vivo study using mouse models with induced highly metastatic hepatocellular carcinoma, treatment with high dose aspirin (0.5%) significantly reduced degree of metastases . In a clAspirin belongs to the class of non-steroidal anti-inflammatory drugs (NSAIDs). Aspirin can inhibit two isoforms of cyclooxygenase (COX), which are responsible for the conversion of arachidonate to prostaglandin G2 and subsequent production of prostaglandin H2 . These pWhile a body of observational and animal studies point to the effects of using aspirin in cancer therapy, more randomized clinical trials are required to verify their anti-tumor function. Several aspects of using aspirin as a cancer treatment remain to be studied. It is unknown whether aspirin along with other cancer treatment options is more effective compared to using aspirin alone. Specific mutations and markers that make certain patient populations more responsive to aspirin treatment have not been identified. Moreover, aspirin use has side effects that must be taken into account, especially damage to the gastrointestinal tract .Besides aspirin, many other drugs targeting platelets have been proposed to have potential for reducing cancer metastasis. It is worth noting that most of these drugs target processes involved in platelet activation and TCIPA. A 5-nitrobenzoate compound 2CP can bind CLEC-2, which disrupts podoplanin-CLEC-2 interaction and subsequent TCIPA. In vivo, 2CP can reduce the number of metastasis foci in mouse glioma models . The GPIAlthough targeting platelets seems promising to impair cancer progression, there are several challenges of targeting platelets in cancer treatment. The biggest challenge is the versatile functions of platelets. As mentioned above, platelets can have pro-angiogenic or anti-angiogenic and pro-inflammatory or anti-inflammatory effects, and we still have very limited understanding of the conditions that stimulate the different platelet functions. As a result, it is difficult to predict the exact consequences a drug blocking platelet activation will have. Moreover, depending on the dose and patient conditions, the same drug can have different effects. Overall, many more basic and clinical research is required for us to benefit from targeting platelets in battling cancer , 84.Despite a few studies pointing at platelets’ role in inhibiting cancer metastasis, overwhelming evidence suggests that platelets play a generally positive role in promoting cancer metastasis. Platelets play a role in almost all processes of cancer metastasis, from promoting EMT in the primary tumor, to protecting CTCs from immune attack and shear stress, and eventually assisting CTC adhesion and extravasation at the metastatic site Fig. . InteresThe positive effects of platelets on metastasis have made them new targets for preventing or attenuating metastasis in cancer patients. Nonetheless, one challenge is that due to platelet’s diverse functions, targeting one pathway involved in platelet’s promotion of metastasis may only have limited effects. However, as many pathways require platelet activation and aggregation, targeting platelet activation and binding may inhibit many pathways used by platelets to promote metastasis. Activated platelets secrete contents in the intracellular granules that contain growth factors such as VEGF and TGFβ, which promote processes such as angiogenesis and EMT in tumor cells. Furthermore, coating of platelets around CTCs following platelet activation protects CTCs from immune attack and shear stress and favors adhesion to the metastatic site. As reviewed above, drugs such as aspirin, which inhibits synthesis of platelet agonist TxA2, shows promising effect on reducing metastasis rate in animal models and clinical trials.Nonetheless, there is still one complication regarding inhibition of platelet activation. Although activation by signals including CLEC-2, ADP and thrombin all lead to key platelet activation pathways such as increase of integrin receptor expression, certain platelet functions may depend upon signaling through certain platelet agonists . For insStudy of platelets’ effects on metastasis continues to expand our understanding of the diversity of platelet functions, and there are still many unanswered questions about the mechanisms through which platelets affect metastasis. New findings made in the future can lead us to more effective ways to combat cancer metastasis.


Identification of regional dysfunction is important for early risk stratification in patients with suspected non-ST-elevation myocardial infarction (NSTEMI). Strain echocardiography enables quantification of segmental myocardial deformation. However, the clinical use is hampered by time-consuming manual measurements. We aimed to evaluate whether an in-house developed software for automated analysis of segmental myocardial deformation based on tissue Doppler imaging (TDI) could predict coronary occlusion in patients with suspected NSTEMI.Eighty-four patients with suspected NSTEMI were included in the analysis. Echocardiography was performed at admission. Strain, strain rate and post-systolic shortening index (PSI) were analyzed by the automated TDI-based tool and the ability to predict coronary occlusion was assessed. For comparison, strain measurements were performed both by manual TDI-based analyses and by semi-automatic speckle tracking echocardiography (STE). All patients underwent coronary angiography.Seventeen patients had an acute coronary occlusion. Global strain and PSI by STE were able to differentiate occluded from non-occluded culprit lesions  and identify patients with an acute coronary occlusion (AUC 0.66 for both strain and PSI). Measurements of strain, strain rate and PSI based on TDI were not significantly different between occluded and non-occluded territories.Automated measurements of myocardial deformation based on TDI were not able to identify acute coronary occlusion in patients with suspected NSTEMI. However, this study confirms the potential of strain by STE for early risk stratification in patients with chest pain. Identification of regional myocardial dysfunction is important for the early risk stratification in patients with suspected non-ST-elevation myocardial infarction (NSTEMI). Strain echocardiography enables quantification of regional deformation and has evolved as a promising tool to identify patients with suspected NSTEMI who have an occluded culprit coronary artery –6. EchocStrain is mostly analyzed by speckle tracking echocardiography (STE), based on speckle recognition and motion tracking from frame to frame in B-mode images. Modern software allows semi-automatic measurements of STE. Strain can also be calculated by tissue Doppler imaging (TDI), which has the important advantage of higher frame rates . High frA new software capable of extracting tissue velocities from TDI in the apical views, interpolate the velocities into 3D and automatically extract strain and strain rate has been developed . The aimOne hundred thirty-five eligible patients referred to a hospital with suspected NSTEMI with acute anginal pain lasting for ≥ 10 min, a history of < 3 days and indication for coronary angiography according to guidelines  were scrEchocardiographic examinations were acquired using a Vivid 7 scanner . All analyses were performed blinded to angiographic results.([peak cycle strain – end systolic strain] / [peak cycle strain]). Finally, the TDI software estimated the area fraction (%) of the mycoardium with noise values in the TDI signal. Cut-off values for noise were a strain value below − 25% or above 5%.To obtain segmental peak systolic and post systolic strain and strain rate values from the TDI software, manual tracing of the left ventricular contour in the tissue Doppler recordings was first performed for each of the three standard apical views . A commercially available software package  was used for the tracing. The traced positions along the myocardium from the three apical views were extracted from EchoPac and imported into the TDI software. The tissue velocity for each position was extracted from the ultrasound DICOM recording. If the myocardial wall and the manual tracing of the greyscale image was outside of the TDI sector, the TDI beam closest to the traced point was considered. Assuming a 60˚ rotation angle between the views, the TDI software applied cubic spine interpolation to calculate the missing data circumferentially between the views to construct a 3D mesh. A standard 16 segment model was applied to the mesh, subsequently per segment velocity and position data was derived automatically, from which global longitudinal strain (GLS), strain rate and PSS were calculated . The ROI was placed to best fit the myocardial wall in concordance to the six segments in each of the three apical standard views Fig. . Peak sySegmental strain and post-systolic index (PSI) were analyzed by a commercially available speckle tracking software  using the semi-automatic Automated Functional Imaging (AFI) mode. The speckle tracking echocardiography AFI (STE-AFI) software used the three standard apical views and placed the region of interest (ROI) automatically to fit the myocardial wall. The ROI was manually adjusted to best fit the myocardial wall from endocardium to the epicardial border. Special care was taken to not include the pericardium. The tracking quality was visually assessed by comparing the underlying grey scale cine loop with the tracking and the segment was rejected if tracking quality was poor. In a 16-segment model , 12, STETo calculate territorial strain and strain rate values corresponding to the theoretical perfusion area of the main epicardial coronary arteries, both for TDI and speckle tracking, we averaged segmental values corresponding to each territory . A 16-seCoronary occlusion was defined as TIMI flow 0 or 1 in the infarct-related artery. Angiographic findings were matched with corresponding territorial deformation in the 16-segments model.Statistical analyses were performed by STATA/MP 17. Descriptive statistics are presented as n (%) for the categorical variables and mean (SD) or median (IQR) for continuous variables. Continuous territorial variables in the culprit area were compared to the non-culprit area with two-sample t-test using groups. The global measurements were compared by linear mixed model with subject specific random intercept and group specific residual variance. We also did receiver operating characteristic (ROC) analyses to evaluate the diagnostic ability of echocardiographic variables.Of the 100 patients, 11 (11%) examinations could not be analyzed by STE-AFI due to significant heart rate variation between the three views (n = 10) and geometry changes in cine-loop (n = 1). Five (5%) examinations could not be analyzed by the automated TDI software because the tracing in EchoPac was not feasible due to greyscale and TDI incompatibility (n = 2), geometry changes in the cine-loop (n = 1) and technical issues with the DICOM image files (n = 2). The final data set thus consists of 84 examinations  for measurements by STE-AFI, manual TDI and the automated TDI, respectively.The absolute territorial strain values in the culprit territories for patients with NSTEMI were lower for the automated TDI measurements compared to the STE-AFI measurements  and compared to the manual TDI  Table . PSI valSimilarly, for STE-AFI, territorial strain in the culprit territory was significantly impaired in patients with occluded compared to non-occluded culprit lesions for all territories , the same applies to PSI. In contrast, neither the automated TDI software nor manual TDI measurements were able to identify differences in GLS, global longitudinal strain rate or PSI between patients with occluded and non-occluded culprit lesions  and 20 (1%) respectively. Ten randomly selected examinations had an area fraction average of 4% noise. In contrast, with AFI and the manual TDI method, 378 (28%) and 339 (25%) of the segments were excluded due to poor tracking, noise or out of view motion.In this study, the inhouse developed TDI software for automated analysis of strain, PSI and strain rate, was not able to identify acute coronary occlusion in patients with suspected NSTEMI. In contrast, strain by STE-AFI accurately identified coronary occlusion and differentiated the occluded territory from the non-occluded territory, in line with earlier studies –6, 14, tThe automated TDI software provided lower absolute values than both manual TDI-based measurements and the STE-AFI. This is in line with a comparable study with semi-automatic TDI measurements . AnotherAdditionally, due to interpolation from the 2D to the 3D model, missing values including noise and reverberations will be extended into the interpolated area. Furthermore, the automated software always analyzed the second of three consecutive cycles, whereas manual measurements allows the operator to choose the heart cycle with best image quality. Together, these factors probably explain why the TDI measurements had significant lower absolute values than the STE and manual TDI.The image acquisitions consist of numerous frames from each heart cycle. The automated TDI software did averaging of strain values over 5 frames to get more reliable values (current frame and 2 frames back and 2 frames forward as a light form for smoothing). STE smoothing settings are vendor specific and not publicly available. Consequently, we do not know if the smoothing settings are comparable. Smoothing settings will affect the strain measurements . As the Earlier studies have provided conflicting results regarding the diagnostic accuracy of global vs. territorial measurements –21. In tThis study confirms that strain by speckle tracking echocardiography is a useful tool for identification of coronary occlusion in patients with chest pain. Although TDI has theoretical advantages compared to speckle tracking for strain analyses, further research and technical improvements are still needed to overcome the trade-offs between frame rate vs. image quality, and time-consuming measurements vs. clinical feasibility. In future versions of automated TDI software, implementation of an algorithm for automatic rejection of segments with poor tracking or significant reverberations is paramount.TDI is susceptible to noise and reverberations. In contrast to STE-AFI, the automated TDI software did not allow for rejection of segments with poor image or tracking quality. Furthermore, the images were acquired on an older generation ultrasound scanner. Modern scanners are available with the possibility of both better image quality and higher frame rates. It is unclear whether new scanners would affect the results in this study. Also, this material constitutes conventional rest echocardiograms only. Future studies must therefore address how these methods perform when assessing the importance of coronary stenosis during stress echocardiography. Finally, the study sample was relatively small with only seventeen patients with occluded arteries. Despite this, the differences between the automated TDI method and STE-AFI seem to be consistent, and at present, speckle tracking remains the method of choice for automated measurements.Fully automated measurements of myocardial deformation based on tissue Doppler imaging were not able to identify acute coronary occlusion in patients with suspected NSTEMI. In contrast, semi-automatic measurements of strain by speckle tracking accurately identified coronary occlusion and differentiated the occluded territory from the non-occluded territory. This confirms the potential of deformation imaging in the early risk stratification of patients with chest pain, however improved algorithms are still needed to allow for fully automatic measurements.


Low patellofemoral joint (PFJ) contact force has been associated with PFJ osteoarthritis. Quadriceps force and knee flexion angles, which are typically altered after an anterior cruciate ligament reconstruction (ACLR), primarily influence PFJ contact forces. It is still inconclusive whether differences in PFJ contact forces are present during high knee flexion tasks such as side-step cutting after clearance to return to sports (RTS) after ACLR.To explore PFJ contact forces in the ACLR limb and compare them with those of the contralateral and control limbs during side-step cutting tasks after clearance to RTS.Controlled laboratory study.A total of 26 male athletes with ACLR who were previously cleared to RTS were matched with 23 healthy men serving as the control group. Three-dimensional motion capture and force plate data were collected while both groups performed anticipated side-step cutting tasks. Joint kinematics, kinetics, muscle forces, and PFJ contact forces were calculated using musculoskeletal modeling.P < .001) and the control limbs . During peak PFJ force, knee flexion angle was lower in ACLR limbs compared with the contralateral  and control  limbs. A lower quadriceps force compared with the contralateral  and control  limbs was also found.Peak PFJ force was lower in the ACLR limbs compared with the contralateral limbs (mean difference [MD], 5.89 body weight [BW]; 95% CI, 4.7-7.1 BW; Lower PFJ contact forces and a combination of quadriceps force deficits and smaller knee flexion angle were found in the ACLR compared with the contralateral and control limbs even after clearance to RTS.Despite rehabilitation and subsequent clearance to RTS, differences in PFJ contact forces are present after ACLR. Current rehabilitation and RTS battery may not be effective and sensitive enough to identify and address these differences. Typical management of an ACL rupture usually includes ACL reconstruction (ACLR) followed by ~6 to 12 months of rehabilitation, with the goal of restoring knee joint stability. Despite this, poor patient-reported outcomes related to knee function, high reinjury risk, and accelerated onset of knee osteoarthritis are common after ACLR. The development of knee osteoarthritis has been reported as early as 3 years after ACLR. Given the high rates of ACLR in young athletes (<25 years), early knee joint degeneration can lead to a significant number of young individuals with impaired function and reduced quality of life because of knee osteoarthritis.Rupture of the anterior cruciate ligament (ACL) is one of the most common injuries in the knee. Smaller knee flexion angle and excursion as well as lesser knee extension moments are commonly reported in the ACLR leg compared with the contralateral leg and healthy controls during tasks like gait and running.30 Furthermore, lower knee joint contact forces are common after ACLR,53 with lower knee joint contact force during walking associated with the development of knee osteoarthritis 5 years after ACLR. Most of the studies on knee joint contact force and osteoarthritis risk after ACLR have focused on the tibiofemoral joint.53 However, patellofemoral joint (PFJ) osteoarthritis is reported to be as high as 80% after ACLR and is associated with worse disabilities compared with osteoarthritis in other knee compartments. Therefore, identifying possible mechanisms related to the increased risk of PFJ osteoarthritis may be important to improve patient outcomes after ACLR.Alterations in lower limb biomechanics are common after ACLR. Of these tasks, the side-step cut is one of the most physically demanding and commonly performed tasks in team sports and is a common mechanism of ACL injury. During side-step cutting, large loads in the PFJ can occur because of the high knee flexion angles and quadriceps force commonly seen during the execution of the task. The interaction between knee flexion angle and quadriceps force determines the total compressive forces at the PFJ. Given that quadriceps weakness and reduced knee flexion angle during tasks  are common in individuals who have undergone ACLR, these could potentially lead to alterations in PFJ contact forces. Previous studies have investigated PFJ contact forces after ACLR during walking, running, and single-leg forward hopping.54 The results from these studies suggest that reductions in PFJ contact forces could be secondary to the presence of reduced quadriceps strength, lower peak knee flexion angles, or both, as well as psychological factors related to fear of reinjury and/or instability and compensatory strategies to underload the ACLR limb. However, no study has yet investigated PFJ contact force in individuals who have undergone ACLR and have successfully passed return-to-sports (RTS) criteria . Furthermore, PFJ contact force during a high-demand task like side-step cutting has yet to be examined.Throughout ACLR rehabilitation, individuals progress from normal gait tasks to more dynamic movements such as running, jumping, and side-step cutting.Therefore, the aim of this study was to investigate PFJ contact forces during the performance of a side-step cutting task at the time of RTS clearance in individuals who have undergone ACLR and compare them with those of the contralateral limb and a healthy control group. Our hypothesis was that there would be lower PFJ contact forces in the ACLR limb compared with the contralateral and healthy control limbs.A total of 48 participants agreed to take part in this study : 26 men  that included consideration of the following: (1) clearance from both their surgeon and physical therapist, (2) completion of a sports-specific on-field rehabilitation program, (3) quadriceps strength (limb symmetry index ≥90%), and (4) hop test battery performance (limb symmetry index ≥90%). Participants with concomitant meniscal injury that did not significantly interfere with their rehabilitation were included in the study. Exclusion criteria for the study included full-thickness articular cartilage lesion and any other major lower extremity injury in both legs . The activity levels for the ACLR (before ACL injury) and control groups were assessed using the Tegner Activity Scale. Patient-reported outcomes related to pain, function, and psychological readiness were collected using the International Knee Documentation Committee and Anterior Cruciate Ligament–Return to Sport after Injury questionnaires.The ACLR group was recruited for the study after completing supervised rehabilitation at the Aspetar Orthopaedic and Sports Medicine Hospital and were subsequently enrolled 1 week after receiving RTS clearance. Clearance to RTS was conducted using a shared decision-making strategyRecruitment for the control group was performed using a convenience sampling from a pool of professional and high-level recreational athletes. Inclusion criteria were age between 18 and 35 years, Tegner score ≥7, participation in level 1 or 2 sports (≥3 times per week), no previous lower limb surgery, and no lower limb muscle injury in the 3 months before testing.Data collection for this controlled laboratory study was performed at the biomechanics laboratory of the Aspetar Orthopaedic and Sports Medicine Hospital. Participants were recruited between November 2018 and October 2019. Informed consent was obtained from all participants before participating in the study. This study is part of a larger study investigating RTS criteria after ACLR rehabilitation.Ethics approval for this study was granted . The transfer and use of previously collected and nonidentifiable data was approved by the Australian Catholic University Human Research Ethics Committee (registration No. 2021-29N). Three marker clusters were also placed laterally on the thigh and shank of both legs. Three-dimensional marker trajectories were collected using a 14-camera motion capture system  along with ground-reaction forces using 5 ground-embedded force plates .A total of 43 reflective markers were placed according to a full-body Plug-in Gait marker set that included additional anatomic markers on the sacrum, medial knee, and medial ankle.All participants wore shorts and shoes for data collection. Participants were familiarized with all procedures and tasks before data collection. Before biomechanical testing, participants performed a 7-minute warm-up session composed of running, side running, deep squats, and double-leg jumps.For the side-step cut task, participants started in a standing position 6 m away from the force plates. They were then instructed to accelerate maximally toward the force plates, performing 3 trials of an anticipated 45° side-step cut to the left and to the right. The order of testing for each limb was randomized using a coin toss. For all tests, a clear foot contact of the plant foot (side-step cutting) on the force plate was needed for a trial to be considered successful.38 which include semiautomated analysis via a custom R code  interface with OpenSim Version 4.2. A generic musculoskeletal model was scaled to each individual's anthropometry based on a static trial. An inverse kinematics algorithm was used to calculate joint angles during the side-step cut by means of a weighted least squares optimization that minimizes the difference between model and experimental marker positions during the dynamic trials. Inverse dynamics was used to obtain the generalized forces and moments that are responsible for these movements. Static optimization was used to decompose joint moments into individual lower limb muscle forces by minimizing a cost function (sum of muscle activations squared). To calculate PFJ contact force, we used a separate empirically based model as described previously:Data analysis was performed using previous methods as described by Maniar et al,PFJF is the PFJ contact force, QF is the quadriceps force, PF is the patellar tendon force, and β is the patellar mechanism angle. Note that PF and β were calculated as a function of the knee flexion angle and quadriceps force , based on data from an in vitro study.where  we also calculated the knee flexion angle and quadriceps force at the time of peak PFJ contact force.The peak PFJ contact force was extracted during the stance phase (defined as the raw ground-reaction force exceeding 20 N). Because the primary determinants of the PFJ force are the knee flexion angle and quadriceps force,Appendix Figure A1, available in the online version of this article) and moments  was comparable with that of previous work on side-step cutting in healthy individuals. The temporal characteristics between predicted muscle forces and electromyography (EMG) data from previous work performed throughout the stance phase of the side-step cut  also showed general agreement between model-based predictions and EMG data for most muscles, after accounting for EMG-to-force physiological delays (~100 ms) as per recommendations.Qualitative verification of the temporal-varying characteristics of experimental joint angles (see  An independent-samples t test was used (P≤ .05) to determine between-group comparisons in participant characteristics. A linear mixed-effects model approach was used to determine if differences existed between the ACLR leg and the contralateral leg as well as the healthy control legs for each of the previously described outcome variables. For each linear model, the leg  was modeled as a fixed effect and the participant number modeled as a random effect, while adjusting for approach velocity . Approach velocity was adjusted for, as any variation between groups or trials  could confound analysis if unaccounted for. Where significant effects were found for the limb, we conducted post hoc pairwise comparisons using the Tukey method. Data assumptions  were verified via the visual inspection of qqplots and residual plots. For all analysis, statistical significance was set at P < .05 .ResultsDescriptive statistics were used to summarize participant characteristics. The Shapiro-Wilk test was used to check for normality of distribution of data.P < .001) (P < .001) (P < .001) (P < .004) limbs (P < .001) (P < .001) limbs (P = .281) (P = .768) (P = .080) (Patient characteristics and RTS testing results can be found in  < .001) , Table 2 < .001) , Table 2 < .001) , Table 24) limbs , Table 2 < .001) , Table 21) limbs , Table 2 = .281) , Table 2 = .768) , Table 2 = .080) , Table 2 = .080) .The most important finding of the study was that there were lower PFJ contact forces in the ACLR leg during the stance phase of a side-step cut when compared with the contralateral and healthy control limbs. Additionally, smaller knee flexion angle and lower quadriceps force were found at the time of peak PFJ contact force in the ACLR leg compared with the contralateral and healthy control limbs. As this was the first study to investigate PFJ contact forces during a side-step cut, a comparative data set on the magnitude of our PFJ contact forces is currently not available. However, the magnitude of forces found in this study was not surprising given the larger knee flexion and knee extension moments required to perform a side-step cut compared with the abovementioned tasks. Studies on other activities that require larger knee flexion angles, such as a squat, showed that PFJ contact forces can go up to 18 BW.The PFJ contact forces found in this study (13-19 BW)  were lar54 Similar to our results, lower PFJ contact forces in the ACLR limb were found during the stance phase of walking (3-6 months after ACLR) and running (1-2 years after ACLR)45 as well as the landing phase of a single-leg forward hop (1-2 years after ACLR) compared with the contralateral54 and healthy control groups.46 In contrast, Herrington et al found larger PFJ contact forces during the stance phase of running (~7 months after ACLR), whereas Williams et al found no differences between limbs during walking at 2 years. The differences of our results from these 2 studies could be attributed to the different tasks and time after ACLR. Herrington et al performed their assessments much earlier in the post-ACLR phase compared with our study during running tasks, whereas those of Williams et al were from a less demanding task  at 2 years after ACLR.Previous studies have investigated PFJ contact forces during walking, forward hopping, and running in ACLR limbs compared with non-ACLR limbs.46 One of the proposed explanations for this is the presence quadriceps weakness. The presence of low quadriceps strength could logically explain a subsequent reduction in the ability to produce a knee extension moment. As such, biomechanical compensations such as a smaller knee flexion angle, as seen in the current study, or a relative increase in the joint moments produced at the trunk, hip, and ankle can arise from a reduced knee extension moment.45 Another explanation to the “underloading” of the knee joint in this study could be from psychological factors like pain, fear of reinjury, or psychological readiness. Previous studies have shown associations with low psychological readiness or fear of reinjury with aberrant lower limb biomechanics in individuals who have undergone ACLR.56 The combination of deficits in these physical and psychological capacities could potentially explain the smaller knee flexion angle, knee extension moment, and quadriceps force that resulted in the low PFJ contact forces in the ACLR limb compared with the healthy limbs in this study. However, the participants in this study had a relatively symmetrical isokinetic quadriceps strength limb symmetry index  have been mixed.47 Given this, future work that compares PFJ contact forces after different ACLR graft types may be warranted. Last, this study included a male-only population from a single site, which limits the generalizability of our results to women. Future work in the female population is still needed given the previously reported differences in lower limb strength and biomechanics between the sexes.42We acknowledge that there are limitations to the current study. First, our PFJ contact force model only considered the sagittal plane biomechanics of the patella. Although frontal and transverse plane loading could potentially influence PFJ contact forces, PFJ loading is largely sagittal plane dominant, and the results of our study were relatively comparable with available data.This study found that PFJ contact forces during a side-step cut were lower in the ACLR limb when compared with contralateral and control limbs, despite clearance of athletes to RTS. A combination of reduction in quadriceps force and smaller knee flexion angle was found in the ACLR limb compared with the contralateral and healthy control limbs. Current RTS criteria do not appear effective enough to restore biomechanical alterations in the lower limbs that may predispose individuals who have undergone ACLR to lower PFJ contact forces.Click here for additional data file.Supplemental material, sj-pdf-1-ajs-10.1177_03635465231166104 for Lower Patellofemoral Joint Contact Force During Side-Step Cutting After Return-to-Sports Clearance Following Anterior Cruciate Ligament Reconstruction by Argell J. San Jose, Nirav Maniar, Rodney Whiteley, David A. Opar, Ryan G. Timmins and Roula Kotsifaki in The American Journal of Sports Medicine


Falls and fall-related injuries are significant public health problems in older adults. While balance-controlling strategies have been extensively researched, there is still a lack of understanding regarding how fast the lower-limb muscles contract and coordinate in response to a sudden loss of standing balance. Therefore, this pilot study aims to investigate the speed and timing patterns of multiple joint/muscles’ activities among the different challenges in standing balance. Twelve healthy young subjects were recruited, and they received unexpected translational balance perturbations with randomized intensities and directions. Electromyographical (EMG) and mechanomyographical (MMG) signals of eight dominant-leg’s muscles, dominant-leg’s three-dimensional (3D) hip/knee/ankle joint angles, and 3D postural sways were concurrently collected. Two-way ANOVAs were used to examine the difference in timing and speed of the collected signals among muscles/joint motions and among perturbation intensities. This study has found that (1) agonist muscles resisting the induced postural sway tended to activate more rapidly than the antagonist muscles, and ankle muscles contributed the most with the fastest rate of response; (2) voluntary corrective lower-limb joint motions and postural sways could occur as early as the perturbation-induced passive ones; (3) muscles reacted more rapidly under a larger perturbation intensity, while the joint motions or postural sways did not. These findings expand the current knowledge on standing-balance-controlling mechanisms and may potentially provide more insights for developing future fall-prevention strategies in daily life. Falls are one of the major public health problems in the world. Approximately one in three older adults fall worldwide , and 28.Humans have different patterns of lower-limb joint motions in response to varied intensities of balance perturbations. Previous studies have identified three fundamental strategies to maintain the static standing balance, i.e., the ankle strategy, hip strategy, and stepping strategy . The ankAn investigation of the rapidity and appropriate sequence of movements in the hip, knee, and ankle joints is crucial for understanding the balance-controlling strategy, especially during unexpected and intense balance perturbations. Previous studies have primarily focused on the peak responses of postural sways and joint angles in maintaining standing balance ,12,13, aIn addition to examining the lower-limb joint motions, analyzing the lower-limb muscle activities can provide greater insights into the underlying balance-controlling strategies. Irrespective of the balance-controlling strategy utilized, the acceleration of any body segment resulting from a perturbation must be generated by the contraction of the corresponding skeletal muscles. Most previous studies investigated the signals of only one or a couple of lower-limb muscles for maintaining balance ,19,20,21Meanwhile, one of our recent works investigated the rapid responses of eight dominant-leg muscles following the sudden loss of balance induced by waist-pull perturbations, by quantifying the EMG-onset latency, time to peak EMG amplitude, and rate of EMG rise of the captioned muscles . It mainApart from the joint reactions and muscle electrical activities, the response of other events along the motor output pathway during balance control has been less explored. The generation of a joint motion goes through activation in neuromuscular junctions, muscle mechanical activities , and force propagation to tendons . HoweverTo bridge the above research gaps, this study aimed to explore how healthy young adults respond to the moving-platform-induced balance perturbations with multiple directions and intensities from the perspectives of postural sways, lower-limb joint motions, and lower-limb muscle activities. The objectives of this study were to examine the differences in speed  and peak responses of (1) the forward/backward, medial/lateral, and upward/downward COM displacements; (2) the eight lower-limb joint motions ; and (3) the eight dominant-leg muscles’ electrical and mechanical activities  under the different perturbation intensities. Such comprehensive analysis of kinematics and muscle activities under the sudden loss of balance that simulates daily scenarios is expected to uncover the more in-depth mechanisms underlying standing-balance control. We hypothesized that (1) agonist muscles resisting the induced postural sway would have faster activation than antagonist muscles; (2) involuntary/passive joint motions and postural sways induced by the unexpected perturbation would occur earlier than voluntary/active ones for balance recovery; and (3) higher intensities of unexpected perturbations would induce faster muscle activities, joint motions, and postural sways.No high-intensity sports within 24 h before the experiment;No known neurological or musculoskeletal deficits;No history of balance disorders, walking disorders, or dizziness;No history of lower-limb injuries within a week;No sight or hearing disorders;No medication intake that could affect muscle activities.This is an observational/cross-sectional and exploratory study. A total of 12 young healthy adults aged between 18 to 24 were recruited through the method of convenience sampling. Ethical approval was granted by the Institutional Review Board (IRB) of The Hong Kong Polytechnic University (HSEARS20201230002). The subjects satisfied the following inclusion criteria :No high-A moving-platform perturbation system was developed to induce the unexpected balance perturbations see . It consA three-dimensional capture and analysis system, i.e., the Vicon system , with eight cameras, was applied to capture the whole-body kinematics. The sampling rate was 250 Hz. A total of 39 reflective markers were adhered to the subject’s body based on the full-body plug-in-gait dynamic model, including twelve on the bilateral lower limbs , four on the pelvis , five on the torso , fourteen on the bilateral upper limbs , and four on the head  . To ensuEight major lower-limb muscles’ activities were collected by an eight-channel Trigno Wireless Biofeedback System . Each Delsys Trigno Avanti sensor  consisted of an EMG sensor  and a 3-axis accelerometer  to serve as the MMG sensor . The samEach subject firstly accomplished the demographic data collection and the subjective assessments. Body mass and height were measured using a standard scale , and other anthropometrics such as leg length were measured using a tape measure and a caliper. The International Physical Activity Questionnaire—Short version (IPAQ-S)  and the Before the perturbation experiment, the reflective markers and the EMG and MMG sensors were attached to subjects, and instructions and explanation of the experimental protocol were given. To simulate the daily situation, the subject was asked to wear his/her usual shoes during the whole perturbation experiment. The subject was instructed to stand naturally with two feet shoulder-width apart in the middle of the platform and knees fully extended; subjects were instructed that when the platform moved, he/she should try his/her best to maintain balance without stepping or return to the original foot position as soon as possible if stepped. The subject held a light bar in front of the body at the waist level, and the reflective markers was not blocked during data collection in this way . Dark-coEach subject received a total of 48 unexpected balance perturbations induced by the moving platform (4 directions × 4 intensities × 3 repetitions), and the kinematic, EMG, and MMG data of the subject’s responses were collected. These balance perturbations were randomly allocated into four perturbation trials during the experiment, and there was a 5 min rest between the two trials to avoid the effects of fatigue. For each perturbation, the starting time, direction , or intensity  was random. The direction of a balance perturbation was defined as the moving direction of the platform in reference to the subject’s dominant leg. For example, for a subject with the right leg as the dominant leg, pulling the platform toward the left was regarded as a “medial” perturbation, while pulling toward the right was a “lateral” perturbation see . DiffereThe kinematic data, i.e., the whole body’s center of mass (COM) and the hip, knee, and ankle angles, were firstly processed by the plug-in-gait dynamic model of the Vicon system and then zeroed to the baseline, i.e., mean signal value over the 1000 ms interval before each perturbation via a customized MATLAB program . The COM displacement was further subtracted from the displacement of the platform to obtain the COM displacement relative to the base of support (BOS).For the muscle activity data, the raw EMG data were firstly zeroed to the mean signal value over the whole perturbation trial, then full-wave rectified, and low-pass filtered by a bi-directional 4th-order Butterworth filter (cut-off frequency: 4 Hz) to obtain the EMG signal envelopes . To extrThe onset latency, time to peak amplitude, peak amplitude, and/or rate of rise were analyzed for the kinematic, EMG, and MMG data see . The onsEMG signal difference among the eight different muscles and among the four different perturbation intensities (muscle × perturbation intensity);MMG signal difference among the eight different muscles and among the four different perturbation intensities (muscle × perturbation intensity);Joint angle difference among the eight different joint motions and among the four different perturbation intensities (joint motion × perturbation intensity);COM trajectory difference among the six different postural sway directions and among the four different perturbation intensities .The IBM SPSS version 25 was used for statistical analyses, and the significance level was set as 0.05. For each of the four perturbation directions, two-way analysis of variance and post hoc pairwise comparisons with Bonferroni corrections were applied to analyze the effects of the below two factors on the onset latency, time to peak, peak amplitude, or rate of rise of the investigated signals:The demographic data and the subjective assessment results of 12 subjects are shown in Under the lowest, low, and high perturbation intensities, all young subjects were able to maintain balance without stepping or lifting their feet (0/432). Under the highest intensity of perturbations, eight subjects stepped for a total of 14 times following the anterior perturbations (14/36), no subject stepped following the posterior perturbation (0/36), one subject took a step with the non-dominant leg following the medial perturbation (1/36), and one subject took a step with the dominant leg following the lateral perturbation (1/36). Among the stepping responses following anterior perturbations, six subjects took two steps to maintain balance (7/14), three took one step with the dominant leg (4/14), and three took one step with the non-dominant leg (3/14).n = 12). A red dotted line specifies the start of the balance perturbation (t = 1 s). The mean and standard error  values of onset latencies, time to peak, and peak values are also plotted against the different directions of COM displacement in p < 0.05). Perturbation intensity showed significant effect on the peak COM displacement (p < 0.05) but not on the timing of COM displacement.For each of the four perturbation directions, the initial COM displacement was found in the direction opposite to the perturbation, followed by the COM displacement toward the perturbation significantly . Following posterior perturbations, the significantly shorter time to peak COM displacement was observed in the downward direction compared to the upward/backward/medial/lateral directions (p < 0.05). Following medial perturbations, the COM displacement in the upward direction had significantly earlier onset and significantly shorter time to peak than in downward/forward/backward direction (p < 0.05). Following lateral perturbations, the COM displacement had significantly earlier onset and significantly shorter time to peak in the upward direction than in downward/lateral/forward/backward direction (p < 0.05).The unexpected perturbation also induced the early response of COM displacement in the vertical direction. Following n = 12). n = 12) values of onset latencies, time to peak, and peak values of the dominant-leg joint angles.anterior perturbation was induced, significant differences within joints existed in the angle-onset latencies  and in the time to peak angles . Generally, the peak angles of hip flexion, knee flexion, and ankle dorsiflexion significantly increased with the perturbation intensity (p < 0.05).When posterior perturbation was induced, ankle dorsiflexion had significantly earlier angle onset and significantly shorter time to peak angle than ankle plantarflexion (p < 0.05). Among the eight joint motions, the significantly largest joint motion occurred in hip flexion (p < 0.05). Generally, larger perturbation intensity induced larger dominant-leg joint motions (p < 0.05).When medial perturbation was induced, hip adduction showed the significantly earliest angle onset among the eight joint motions (p < 0.05). Hip adduction also showed significantly shorter time to reach peak angle than hip abduction under the low, high, and highest perturbation intensities (p < 0.05), while ankle dorsiflexion showed significantly shorter time to reach peak angle than ankle plantarflexion under the highest perturbation intensity (p < 0.05). Generally, the peak angles of hip flexion, knee flexion, and ankle dorsiflexion significantly increased with the perturbation intensity (p < 0.05).When lateral perturbation was induced, significant differences within joints existed in both the angle-onset latency and the time to peak angle . Under the low, high, and highest perturbation intensities, hip flexion and knee flexion had significantly larger peak angles than the rest of the joint motions (p < 0.05).When n = 12). n = 12) values of EMG-onset latencies, time to peak EMG amplitude, as well as rate of EMG rise against the eight dominant-leg muscles. anterior movement of the platform, significant differences within the agonist–antagonist muscle pairs were found in EMG-onset latency  and in time to peak EMG amplitude . The rate of EMG rise was remarkably highest for the ankle dorsiflexor compared to the other muscles (p < 0.05).Following sudden posterior movement of the platform, the ankle plantarflexor had a significantly shorter EMG-onset latency compared to the knee extensor, hip extensor, and hip adductor (p < 0.05). Among the eight dominant-leg muscles, the ankle plantarflexor had the significantly largest rate of EMG rise (p < 0.05). Generally, larger perturbation intensities induced significantly shorter EMG-onset latencies (p < 0.05) and a significantly larger rate of EMG rise (p < 0.05).Following sudden medial movement of the platform, significant differences within the agonist–antagonist muscle pairs were found in EMG-onset latency  and time to EMG peak amplitude . The ankle dorsiflexor had generally the largest rate of EMG rise among the eight dominant-leg muscles under the low, high, and highest perturbation intensities (p < 0.05). Generally, larger perturbation intensities induced significantly shorter EMG-onset latencies (p < 0.05) and significantly shorter time to EMG amplitude (p < 0.05); for the ankle dorsiflexor, ankle plantarflexor, and hip abductor, the rate of EMG rise also significantly increased with the perturbation intensity (p < 0.05).Following sudden lateral movement of the platform, significant agonist–antagonist differences were found in EMG-onset latency  and in time to peak EMG amplitude . Among the eight dominant-leg muscles, the ankle dorsiflexor had the significantly largest rate of EMG rise (p < 0.05). Generally, larger perturbation intensities induced significantly shorter EMG-onset latencies (p < 0.05), a shorter time to peak EMG amplitude (p < 0.05), and a larger rate of EMG rise (p < 0.05).Following sudden n = 12). n = 12) values of MMG-onset latencies, time to peak MMG amplitude, as well as rate of MMG rise against the eight dominant-leg muscles.p < 0.05). Such an MMG-onset pattern  was observed following all the four directions of balance perturbations. Moreover, following the balance perturbations in the frontal plane, the hip abductor was in the queue with early onset of the MMG signal. Larger perturbation intensities induced significantly shorter MMG-onset latencies (p < 0.05), a shorter time to peak MMG amplitude (p < 0.05), and a larger rate of MMG rise (p < 0.05).In general, the onset of MMG signals was significantly earlier in ankle muscles than in knee or hip muscles . Significant differences within the agonist–antagonist muscle pairs were found in MMG-onset latency  and in time to peak MMG amplitude . No specific trend was observed when comparing the rate of MMG rise among muscles.Following sudden posterior perturbation, the ankle dorsiflexor and ankle plantarflexor had the significantly shorter MMG-onset latencies compared to the other muscles (p < 0.05).Following sudden medial perturbation, the ankle dorsiflexor, ankle plantarflexor, and hip abductor had significantly shorter onset latencies than the remaining dominant-leg muscles (p < 0.05). Significant differences within the agonist–antagonist muscle pairs were found in both the MMG-onset latency and the time to peak MMG amplitude .Following sudden lateral perturbation, the ankle dorsiflexor, ankle plantarflexor, and hip abductor had significantly shorter onset latencies than the remaining dominant-leg muscles (p < 0.05). Additionally, among the eight dominant-leg muscles, the hip abductor had the shortest time to peak MMG amplitude (p < 0.05).Following sudden Via the synchronized capture of eight dominant-leg muscles’ electrical and mechanical activities , eight dominant-leg joint motions (angles), and whole-body postural sways (COM displacements), this study is novel in its comprehensive investigation of the timing and the speed of combined reactions in hip, knee, and ankle muscles and joints following unexpected horizontal/translational perturbations with different intensities and directions. In agreement with our hypothesis 1, this study has observed that (1) agonist muscles resisting the perturbation-induced postural sway activated more rapidly than antagonist muscles, and among the eight dominant-leg muscles, ankle muscles’ large rate of activation contributed the most to resisting the perturbations in both sagittal and frontal planes. However, our hypotheses 2 and 3 were not entirely supported, as results showed that (2) fast responses existed not only in those lower-limb joint motions and COM displacements that were passively/involuntarily induced by the perturbation but could also occur in those actively/voluntarily generated ones to counteract the perturbation; and (3) a larger perturbation intensity evoked the more rapid muscle activities but did not induce faster joint motion or postural sway.These findings build on our knowledge of how fast the hip/knee/ankle muscles can activate and how the lower-limb joints can coordinate to maintain reactive standing balance in healthy young adults. This potentially facilitates the understanding of strategies regarding how humans cope with the varying challenges of losing balance in daily life, which could provide further evidence and guidance for the development of fall-prevention approaches in the future; the details are discussed below.The primary finding of this study was that earlier EMG onset and shorter time to peak EMG amplitude occurred in muscles that could resist the involuntary COM shift induced by the unexpected moving-platform perturbations. On top of this, this study may highlight the great contribution of ankle muscles’ large rate of activation in balance maintenance under unexpected perturbation in both the sagittal and frontal planes.anterior movement of the platform, while the COM had a firstly posterior shift relative to the BOS, the ventral muscles that could rotate the body forward  had a generally earlier onset of activation and shorter latency to reach peak activation compared to the dorsal muscles. These observations are consistent with the previously reported EMG-onset patterns  [Following the unexpected  flexor) ,14,45 an flexor) . On top  flexor) .posterior movement of the platform, the dorsal muscle (ankle plantarflexor) showed an early onset of activation and quick reaching of peak activation to resist the induced forward COM displacement relative to BOS. This agreed with the previous findings that gastrocnemius and hamstrings had faster [Following the unexpected d faster  and gread faster ,46 muscld faster  and prevd faster .medial movement of the platform, the hip abductor was evoked earlier and reached the peak activation earlier than the hip adductor to resist the induced lateral moving of the COM relative to the BOS. The result is consistent with previous studies that reported the significant relationship between the hip abductor and balance recovery under lateral waist-pull perturbations [Following the unexpected rbations ,47,48. Irbations ,50,51. Slateral movement of the platform, the hip adductor reached peak activation earlier than the hip abductor to counteract the sudden medial moving of the COM relative to the BOS. Moreover, among the eight dominant-leg muscles, the ankle dorsiflexor had the greatest rate of activation. These findings were consistent with previous studies that indicated the essential contributions of ankle and hip muscles in controlling mediolateral postural balance [Following the unexpected  balance ,22,49,52 balance .To the authors’ knowledge, no previous study has investigated the activation pattern of all the major hip, knee, and ankle muscles to maintain balance over the unexpected platform movement. By examining the hip adductor/abductor, hip flexor/extensor, knee flexor/extensor, and ankle dorsiflexor/plantarflexor simultaneously, this study identified the essential importance of ankle muscles’ rapid activation in resisting horizontal perturbations for young adults. It is also expected that this study’s more comprehensive and in-depth investigation in the eight leg muscles’ activities could facilitate the future development of programs and assistive devices to improve balance and prevent falls in older adults ,62,63,64The secondary finding of this study was that the rapid responses of lower-limb joint motions and postural sways varied in different directions of balance perturbations. Following the unexpected platform movement, lower-limb joint motions caused by the inertia of body segments were generally the first to appear and are considered as passive/involuntary, while sometimes, other active/voluntary joint motions could also appear as early as the passive/involuntary ones. Among the six directions of COM displacement, COM moving toward the opposite direction of the balance perturbation was generally the earliest because of inertia, which is consistent with the previous studies’ findings ,58,65, wEarly onset of joint angles and short time to peak angles were generally observed in the passive/involuntary joint motions induced by the moving platform. Specifically, because of inertia, faster responses of ankle dorsiflexion (compared to ankle plantarflexion) , hip addanterior perturbation, the passively/involuntarily induced ankle plantarflexion was accompanied by the consistently early onset of hip flexion (compared to hip extension). A previous study also reported that early ankle plantarflexion was followed by the knee flexion, and hip flexion under the sudden forward movement of platform [posterior perturbation, no consistently fast response within the knee or hip joint accompanied the passively/involuntarily induced ankle dorsiflexion. However, a previous study reported that young adults also had an earlier hip extension than hip flexion apart from the ankle joint motions following the posterior moving-platform perturbation [medial perturbation, all the active/voluntary joint motions appeared after the passively/involuntarily induced hip adduction. The hip abduction was corrective, as the muscle activity of the hip abductor was detected, which could work to oppose the passive hip adduction. This reaction was also supported by a previous study that found the corrective response of hip abduction momentarily following perturbations in frontal plane [lateral perturbation, the passively/involuntarily induced hip abduction was accompanied by the consistently early onset and short time to peak of hip flexion, knee extension, and ankle dorsiflexion. Similar to the medial perturbation, the hip adductor muscle worked to oppose the passive hip abduction and produce the later corrective hip abduction [The timing patterns of active/voluntary lower-limb joint motions were different following the four directions of unexpected balance perturbations. Specifically, under the unexpected platform . On top urbation . This maurbation ,22. Theral plane . Under tbduction . In addianterior perturbation, the earlier upward COM displacement (compared to downward direction) seemed to be related to the great proportion of subjects’ stepping strategies and toe-rise strategies in the study. Following the medial or the lateral perturbation, the faster responses of hip flexion, knee flexion, and ankle dorsiflexion in the unloaded leg were observed. The fast upward COM displacement could be caused by the lifting of the unloaded leg. By contrast, following the posterior perturbation, the COM reached peak displacement more quicky in the downward direction than in the upward direction. This response was considered to be passive, as the downward and the passively induced forward postural sways had similar onset latencies and time to peak. The posterior displacement quickly induced the subject’s forward inclined posture, so the COM had a firstly downward displacement and was followed by a later upward displacement to recover the upward posture. Difference in perturbation intensities may explain why the initial COM displacement in the vertical direction following posterior perturbations differed from that following anterior/medial/lateral perturbations. Posterior perturbations were set with smaller intensities than the anterior/medial/lateral perturbations in this study. The latter ones were challenging enough and induced the faster active/voluntary reactions that elevated the COM, while the former ones did not.The unexpected horizontal perturbation also induced the consistently faster response of COM in the vertical direction. As far as the authors know, previous studies have rarely compared the timing of postural sways in horizonal and vertical directions following a balance perturbation. Specifically, in this study, the faster upward COM displacements (compared to the downward direction) were observed following the anterior, medial, and lateral balance perturbations, while the posterior perturbation induced a faster downward COM displacement. Following the The tertiary finding of this study was that larger perturbation intensity induced an earlier EMG onset, shorter time to peak EMG amplitude, and larger rate of EMG rise in the dominant-leg muscles but did not lead to faster responses in postural sways or lower-limb joint motions. This may suggest that under a larger unexpected challenge to loss of balance, the lower-limb muscles could activate earlier and more rapidly to restrict excessive joint motions and prevent excessive COM shifts out of the BOS.The results in this study indicate that the response rate of lower-limb muscles could be related to perturbation intensity in general. EMG-onset latencies and time to peak EMG amplitude were significantly longer under the smaller perturbation intensities than under the higher ones. Previous studies have reported such a phenomenon mainly in the sagittal plane (anterior and posterior directions) ,14,46,66postural sways, this study found that larger perturbation intensity generally induced larger COM displacement along the line of perturbation direction. An example was that both the forward and the backward peak COM displacements increased with the anterior perturbation intensity. This was understandable since the different perturbation intensities in the study were position-controlled. However, a larger intensity of perturbation did not evoke an earlier onset or shorter time to peak COM displacement. A similar amount of time was required to reach a larger postural sway under the greater perturbation intensity. This result partly agreed with a previous study that showed increasing peak COM velocity and peak COM acceleration with perturbation intensity [lower-limb joint motions, it was found that ankle dorsiflexion, knee flexion, and hip flexion angles increased with the perturbation intensity for all the four perturbation directions. Such strategies seemed to be able to reduce the additional horizontal excursions when the challenge to loss of standing balance became larger [A larger perturbation intensity could evoke larger responses in lower-limb joint motions and postural sways; however, it may not be able to evoke faster kinematic responses. For the ntensity . For thee larger . Howevere larger .Attempts have also been made to process and analyze the MMG signals, aiming to examine the possible delays between the electrical and mechanical muscle activities in response to unexpected balance perturbations. A new processing method was used upon optimizing the one reported in our previous study . HoweverWhen comparing among the eight muscles, the onset of the MMG signal under all directions of perturbation was significantly earlier at distal than proximal muscles. Such onset might be caused by the perturbation induced from a moving platform supporting standing, i.e., at the distal side of subject’s body. This is further supported by the result that the value of each parameter in MMG recorded greatly depended on pulling intensity but not for muscles or pulling directions. Although MMG showed considerable reliability to detect muscle activities in static conditions ,73, it mThis study has the below strengths. Firstly, the moving-platform perturbation system was synchronized with the Vicon system and the Trigno Wireless Biofeedback System, enabling our accurate analyses of the temporal parameters of multiple signals during balance control. Secondly, the perturbation intensity  was set as a percentage of the subject’s body height so that the perturbation was a consistent challenge to postural balance across different individuals. Thirdly, this study comprehensively analyzed how fast the eight major leg muscles’ activation and eight lower-limb joint motions could occur during balance control. These findings in healthy young adults can serve as the foundation and reference for not only further studies of balance-controlling mechanisms in older adults with high fall risks, but also the further development of assistive/robotic devices for targeted balance training and fall prevention.There are some potential limitations of this study. Firstly, only a small number of subjects were recruited for this pilot study. Future studies in older adults or a specific population should justify the sample size to make the findings more representative. Secondly, during the processing of EMG signals, this study used baseline EMG value in normal standing for normalization. Therefore, it should be noted that the rate of EMG rise in this study was based on the muscle-activation level in normal standing rather than the capacity of muscle activation. Maximal voluntary contraction (MVC) tests could be carried out in the future to examine if the amplitude-normalization methods affect the finding. Lastly, the current MMG processing method might still be not mature enough to extract the exact vibrations of lower-limb muscles. Further observation and development are needed. More tests could be performed on MMG to evaluate the reliability and validity of reflecting the mechanical muscle activities following the unexpected perturbation.To conclude, among the eight dominant-leg muscles, the ankle muscles’ rapid activation contributed the most to resisting the unexpectedly induced postural sways in both the sagittal and frontal planes. Fast responses of the lower-limb joint motions and the vertical postural sways were related to the perturbation direction. Under a larger perturbation intensity, muscles reacted more rapidly, while joint motions or postural sways were not necessarily faster. These findings provide new insights on the sequence or the fast responses of multiple lower-limb muscles/joints in coping with the different levels of balance challenges. The mechanisms underlying reactive standing balance are thus better understood, which may facilitate future research on developing targeted balance-training protocol and/or technology or devices for fall prevention in older adults.


Secondary infections can occur during or after the treatment of an initial infection. Glucocorticoids may decrease mortality in patients with severe COVID-19; however, risk of secondary infection is not well described. Our primary objective was to investigate the risk of secondary infection among critically ill patients with COVID-19 treated with glucocorticoids. We examined patients with COVID-19 being treated in the intensive care unit at two academic medical centers from 1 to 7/2020. One hundred-seven patients were included. Of these, 31 received steroids and 76 patients did not. Analysis of the larger cohort was performed followed by a matched pairs analysis of 22 steroid and 22 non-steroid patients. Secondary infection was seen in 14 patients (45.2%) receiving steroids compared to 35(46.1%) not receiving steroids (p = 0.968). Secondary infections were most frequently encountered in the respiratory tract. Escherichia coli and Staphylococcus aureus were the most frequently identified organisms. Mortality was 16.1% in the steroid-treated group compared to 23.7% in the control group (p = 0.388). After performing matched pairs analysis and multivariable logistic regression there was no significant difference between secondary infection or mortality and steroid receipt. Secondary infections were common among critically ill patients with COVID-19, but the incidence of secondary infection was not significantly impacted by steroid treatment. Many different types of pharmacological therapies have been trialed in the treatment of COVID-19 with mixed success. The landmark Dexamethasone in Hospitalized Patients with COVID-19  indicated a significant mortality reduction in critically ill patients hospitalized with COVID-19 treated with dexamethasone compared to placebo. Subsequent real-world cohort studies have replicated the positive impact of steroids in severe COVID-19. Although evidence points to steroids being beneficial in the treatment of COVID-19 patients requiring respiratory support, the risks, benefits, and optimal doses are not fully characterized. Prior reports from observational studies have suggested that steroids may have deleterious effects on viral illnesses such as influenza.7 There are also clearly difficulties in assessing the efficacy of steroids in retrospective studies given that the patients with the highest perceived mortality risk are disproportionately treated with steroids. This so-called “confounding by indication” may suggest underlying disease for which steroids are given contributes to poor outcomes rather than the steroids per se.The COVID-19 pandemic has led to devastating consequences for afflicted patients, communities, and healthcare infrastructures. One clinical manifestation is the development of acute respiratory distress syndrome (ARDS) from severe COVID-19.811Secondary infections can occur during or after the treatment of an initial infection. Given the immunomodulatory effects of steroids, there is concern that the use of glucocorticoids may increase the risk of secondary infections. Based on reports of fungal secondary infections in COVID-19 patients, we examined patients prior to the RECOVERY publication to assess the potential impact of glucocorticoid use.12 However, the reports acknowledged uncertainty about adverse event rates due to variable definitions and inconsistent reporting of serious adverse effects across studies. The Adaptive COVID-19 Treatment Trial-4 (ACTT-4) comparing Baricitinib versus dexamethasone for adults hospitalized with COVID-19 showed no increase in new infections in the steroid-treated group. However, other reports of secondary infections including bacteremia, ventilator-associated pneumonia (VAP) and pulmonary aspergillosis in patients with COVID-19 receiving corticosteroids indicate additional studies of adverse events are warranted.15Two recent meta-analyses of randomized trials found consistent benefits of steroids in COVID-19 without any major adverse effects.Identifying this gap in the literature, we sought to characterize the relationship between steroid use and secondary infections in patients with COVID-19. Specifically, we tested the hypothesis that steroids may increase the risk of secondary infections among critically ill patients with COVID-19. In addition, we sought to investigate confounding by indication by examining the outcomes of patients who received steroids following recognized secondary infection.NEJM, after which dexamethasone therapy became the standard of care in critically ill patients with COVID-19.16 Patient confidentiality was protected using de-identified numbers and the study was approved by the UCSD institutional review board . Consent was waived by the IRB. Procedures were followed in accordance with the ethical standards of the responsible committee on human experimentation  and with the Helsinki Declaration of 1975. Inclusion criteria consisted of 1) Patients who tested positive for COVID-19 by nasopharyngeal swab using Nucleic Acid Amplification Test/Reverse Transcription-Polymerase Chain Reaction (NAAT/RT-PCR) techniques according to the Centers for Disease Control and Prevention (CDC) guidelines and 2) critically ill patients defined by meeting clinical criteria for admission to the ICU. There were no specific exclusion criteria.This was a retrospective cohort study of 129 consecutive patients with COVID-19 admitted to the ICU at two large, tertiary care, academic medical centers between January 2020 and July 2020. The enrollment time interval was selected because it preceded the release of the RECOVERY trial in Aspergillus galactomannan , sequential organ failure assessment (SOFA) score on ICU day 0, and 28-day mortality. Microbiologic data documenting specific organisms were also reported as descriptive data although single blood cultures with common contaminant organisms were not included. Culture collection was driven based on the clinical course of the patient or suspicion of infection.Data on 129 patients were retrieved from the electronic medical record manually by trained physicians. These data included: demographics , body mass index (BMI), average daily steroid dose , hospital day at which the steroid was administered, hospital day at which secondary infection was detected, the total number of positive cultures , use of antibiotics at the time of, or in response to, a positive culture, positive To assess better the risk of secondary infections associated with steroids, and to account for confounding by indication, only patients who received steroids prior to the first positive culture were included in the steroid group for the primary analysis. If the timing of steroid and secondary infection was unclear by chart review the case was excluded. If patients received steroids after a positive culture, they were analyzed separately as an exploratory analysis to assess confounding by indication of mortality.In total, we analyzed the 107 patients who met our criteria for the primary analysis. To adjust for the impact of age group and severity of illness (assessed by SOFA score) on outcomes, for a subset, we utilized a matched pairs design to compare secondary infection and mortality in patients treated with and without steroids. In addition, we performed multivariable logistic regression as another method to assess the relationship between the use of steroids and the incidence of secondary infection and mortality in the larger cohort. The remaining 19 patients who received steroids after documentation of secondary infection were analyzed separately out of interest for potential confounding by indication.a priori important covariates including SOFA score and age to allow matched comparisons between steroid and non-steroid-treated groups. For the larger cohort, logistic regression, both adjusted and unadjusted odds ratios were calculated. In the adjusted model age, sex, BMI, and SOFA score were selected as covariates based on a priori criteria. The Hosmer-Lemeshow test was used to assess for goodness of fit. We compared dichotomous variables using a chi-squared test and for non-normally distributed data we utilized non-parametric tests. P-values <0.05 were considered statistically significant. Statistical analyses were performed using IBM SPSS Statistics for Mac OS .The primary outcome was secondary infection defined by a new positive blood, sputum, and/or urine culture requiring treatment with antibiotics. The secondary outcome was 28-day mortality from day zero of admission to the ICU. The explanatory variable of interest was glucocorticoid therapy. For matched pairs analysis, we defined 2 (SD 6.8). In this cohort, patients not treated with steroids had a 46.1% rate of secondary infection compared to 45.2% of patients treated with steroids (p = 0.968)  . Mortali= 0.968) . After p= 0.968) . Mortali= 0.968) .In patients receiving steroids, there was no significant difference in the average daily steroid dose  in patients who did not develop secondary infection compared to patients who did develop secondary infection .Escherichia coli and Staphylococcus aureus were the most frequently isolated causative organisms. The respiratory site was the most common source of secondary infection (43.4%). No Aspergillus species were identified on culture and no positive galactomannan tests were reported for the patients enrolled. Cultures were obtained on average 7 days (SD 7) into the hospitalization. Additional detailed microbiologic data including microorganisms and infection source are summarized in Of patients with positive microbiologic data including urine, blood, or respiratory cultures, Of the group who received steroids after documentation of secondary (n = 19) infection, mortality was 57.9% compared to the group who received steroids prior to secondary infection (n = 31) where mortality was only 16.1% (p = 0.004). The group who received steroids after secondary infection compared to the group who received steroids before secondary infection was significantly older  and mostly male . SOFA scores and comorbid conditions  were not significantly different between groups. Other data regarding a risk of secondary infection and steroid use in patients with COVID-19 use are mixed.19 Thus, we and others have been concerned about the possibility of steroid-induced superinfection in vulnerable patients.15 Our data add to the existing literature by providing some assurance that steroids do not increase risk of secondary infection in critically ill patients with COVID-19.Our findings are important for several reasons. First, we have conducted a comparison of patients with COVID-19 who did and did not receive steroids and observed no increase in secondary infection associated with steroid administration. At baseline, patients who received steroids were younger and more likely to be female; however, after adjusting for age and gender via statistical analyses there was no difference in secondary infection between groups. On further analysis, matching major covariates including SOFA score as a marker of severity of illness and age we again found no difference between steroid use and secondary infection. Additionally, among the patients who received steroids (n = 31) we observed only three deaths in the group who developed secondary infection and two deaths in patients who did not develop secondary infection. We are reassured by this finding as it suggests that the development of secondary infection after receipt of steroids is not independently associated with increased mortality. Our data are helpful particularly when put into the context of the existing literature. The RECOVERY trial showed benefits to dexamethasone for critically ill patients with COVID-19 but did not report data regarding the incidence of secondary infection.Aspergillus infection in our cohort due to concerns about steroid-induced susceptibility. We did not find any evidence of Aspergillus infection in our patient cohort which differs from other studies that reported rates of invasive pulmonary aspergillosis infection of 20–30% in critically ill patients with COVID-19.21Second, we provide data describing the microbiologic prevalence of organisms contributing to secondary infection and specifically looked for 23 and type of steroid to be used. Currently, in the acute setting, hospitalized patients requiring supplemental oxygen, dexamethasone 6 mg daily for 10 days is recommended by the National Institute of Health COVID-19 treatment guidelines. In our cohort, glucocorticoid use and adjusted daily dose of glucocorticoid were not independently associated with an increased risk of secondary infection. Our data may provide some guidance in the design of future studies regarding optimal steroid dosing.26Third, questions remain regarding the safety, tolerability, optimal dosing/timing,28 The concern with such studies is due to ‘confounding by indication’ whereby sicker patients are given steroids (for example steroids given in the setting of shock) and thus poor outcomes may be a function of severity of illness rather than steroids per se. To our knowledge, no large, randomized trials have shown poor outcomes with steroid therapy in influenza infection. Our study design helps to mitigate the concern about confounding by indication since we analyzed separately patients who received steroids after established secondary infection (‘late’ steroids). Mortality in the “late” steroid group was 57.9% (considerably higher than our study participants), emphasizing the importance of addressing confounding by indication and the need for randomized trials to draw rigorous conclusions. In addition, mortality was not significantly different between our steroid and non-steroid groups, providing reassurance regarding steroid therapy in COVID-19.Some observational studies have suggested the potential deleterious effects of steroids on viral illness. For example, steroids have been associated with worse outcomes in influenza pneumonia compared to patients who do not receive steroids. although this practice requires further study but may yield more positive  culture results. Despite these limitations, we believe our study has several strengths and hope that it encourages further research in this important area.Despite our study's strengths, we acknowledge some limitations. First, although our cohort of 107 patients is reasonable, we had only a modest sample size for comparison after matching and the sizes of the steroid-treated subgroups were small. Thus, we may have had limited power to make definitive conclusions, but believe our findings still provide some reassurance regarding the use of steroids in COVID-19. Second, we did not conduct a randomized trial, so the possibility exists for residual confounding. We did our best to control for known covariates such as age and SOFA score as markers of illness severity. Nonetheless, we are highly supportive of further randomized trials to assess the optimal use and associated risk of steroids in critically ill patients. Third, given the retrospective nature of our design, we relied on clinicians to obtain culture data whenever clinically indicated. We cannot exclude whether sub-clinical infections were occurring or indeed whether important superinfections were missed based on our design. Also, we do not have details regarding central line, Foley catheter usage, or duration of mechanical ventilation which may influence the risk for secondary infection. Some centers have suggested the use of surveillance bronchoscopy prior to initiating steroidsDespite considerable research, the therapeutic options for COVID-19 remain limited. Our data provide some confidence that the use of glucocorticoids in the treatment of these patients is likely safe. Although we are highly supportive of larger well-controlled studies, our findings may suggest that steroids are unlikely to predispose to secondary infections. Fungal superinfection does not appear to be a major concern based on our findings.