OBJECTIVE: The purpose of this study was to provide updated data on oncologic outcomes following definitive surgical treatment of soft tissue sarcoma of the hand in a cohort of 109 patients, as well as to characterize risk factors for poor oncologic and functional outcomes.
METHODS: We analyzed data from 109 consecutive patients who had definitive surgical treatment for soft tissue sarcoma of the hand performed between 1996 and 2019 by a single surgeon at a sarcoma center. Primary outcomes included functional outcome (assessed by Musculoskeletal Tumor Society scores), disease-free survival (DFS), and overall survival (OS). We compiled descriptive data and used a multivariable linear model to identify factors associated with functional outcomes. Kaplan-Meier methods were used to estimate 5- and 10-year DFS and OS.
RESULTS: Patients had a median age of 36 years at presentation. Median follow-up was 6.1 years among patients alive at the end of follow-up. The median Musculoskeletal Tumor Society score was 29; functional outcome was worse among patients with high-grade tumors or complications. Among the 107 patients who became disease-free, there were four local recurrences (one with metastasis), six distant recurrences, and one death without recurrence. All local recurrences were deep tumors (two myxofibrosarcoma and two myxoinflammatory fibrosarcoma). Estimated 5- and 10-year DFS rates were 89% (95% confidence interval [CI]: 83% to 96%) and 88% (95% CI: 80% to 95%). There were seven deaths, and the estimated 5- and 10-year OS rates were 95% (95% CI: 90% to 100%) and 92% (95% CI: 84% to 100%). Larger tumor size and higher stage at diagnosis were associated with shorter DFS and OS in univariable analyses; low event rates precluded multivariable analysis of survival.
CONCLUSIONS: Aggressive disease-specific surgical and multidisciplinary treatment can yield long DFS and OS, and good functional outcomes. However, complications and high-grade tumors are associated with worse functional scores.
METHODS: Prognostic II.

OBJECTIVE: Our purpose was to compare differences in the incidence of amyloid deposition in tenosynovium (TS) versus transverse carpal ligament (TCL) biopsies obtained during open carpal tunnel release. We hypothesized that the incidence of amyloid would be similar between TCL and TS when obtaining both specimens from the same patient.
METHODS: All primary, elective open carpal tunnel release cases that underwent biopsy for amyloid between January 2022 and September 2023 were reviewed. Tenosynovial and TCL specimens were independently evaluated by a pathologist to assess for amyloid. Demographic data were collected, and incidence of amyloid deposition was compared between the two samples. Agreement statistics, sensitivity, and specificity were calculated for TCL, using TS as the reference standard.
RESULTS: A total of 196 cases met either Tier 1 (n=180) or Tier 2 (n=16) biopsy criteria. Forty-eight cases were excluded for missed biopsies or laboratory processing errors, leaving 148 cases available for analysis. Amyloid deposition was present in 31 out of 148 (21%) TS specimens and 33 out of 148 (22%) TCL specimens. Overall, the results of the TS biopsy agreed with TCL biopsy in 138 out of 148 cases (93%). In the 10 cases for which the results of the TCL and TS biopsy differed, six cases had (+) TCL and (-) TS, and four cases had amyloid deposition in TS without evidence of deposition in the TCL. Sensitivity and specificity values for the TCL specimen were 87% and 95%, respectively. Positive and negative predictive values were 82% and 97%, respectively.
CONCLUSIONS: For cases of open carpal tunnel release undergoing biopsy, amyloid deposition was noted in 21% of TS specimens and 22% of TCL specimens. Results of TS and TCL biopsies obtained from the same patient agreed in 93% of cases. Single-source biopsy for amyloid represents a reasonable diagnostic approach. Future cost analyses should be performed to determine whether the addition of two biopsy sources to improve diagnostic accuracy is justified.
METHODS: Prognostic II.

Coxsackievirus B1 (CVB1), an enterovirus with multiple clinical presentations, has been associated with potential long-term consequences, including hand, foot, and mouth disease (HFMD), in some patients. However, the related animal models, transmission dynamics, and long-term tissue tropism of CVB1 have not been systematically characterized. In this study, we established a model of CVB1 respiratory infection in rhesus macaques and evaluated the clinical symptoms, viral load, and immune levels during the acute phase (0-14 days) and long-term recovery phase (15-30 days). We also investigated the distribution, viral clearance, and pathology during the long-term recovery period using 35 postmortem rhesus macaque tissue samples collected at 30 days postinfection (d.p.i.). The results showed that the infected rhesus macaques were susceptible to CVB1 and exhibited HFMD symptoms, viral clearance, altered cytokine levels, and the presence of neutralizing antibodies. Autopsy revealed positive viral loads in the heart, spleen, pancreas, soft palate, and olfactory bulb tissues. HE staining demonstrated pathological damage to the liver, spleen, lung, soft palate, and tracheal epithelium. At 30 d.p.i., viral antigens were detected in visceral, immune, respiratory, and muscle tissues but not in intestinal or neural tissues. Brain tissue examination revealed viral meningitis-like changes, and CVB1 antigen expression was detected in occipital, pontine, cerebellar, and spinal cord tissues at 30 d.p.i. This study provides the first insights into CVB1 pathogenesis in a nonhuman primate model of HFMD and confirms that CVB1 exhibits tissue tropism following long-term infection.

Electromyography-based gesture recognition has become a challenging problem in the decoding of fine hand movements. Recent research has focused on improving the accuracy of gesture recognition by increasing the complexity of network models. However, training a complex model necessitates a significant amount of data, thereby escalating both user burden and computational costs. Moreover, owing to the considerable variability of surface electromyography (sEMG) signals across different users, conventional machine learning approaches reliant on a single feature fail to meet the demand for precise gesture recognition tailored to individual users. Therefore, to solve the problems of large computational cost and poor cross-user pattern recognition performance, we propose a feature selection method that combines mutual information, principal component analysis and the Pearson correlation coefficient (MPP). This method can filter out the optimal subset of features that match a specific user while combining with an SVM classifier to accurately and efficiently recognize the user\'s gesture movements. To validate the effectiveness of the above method, we designed an experiment including five gesture actions. The experimental results show that compared to the classification accuracy obtained using a single feature, we achieved an improvement of about 5% with the optimally selected feature as the input to any of the classifiers. This study provides an effective guarantee for user-specific fine hand movement decoding based on sEMG signals.

Muscles play an indispensable role in human life. Surface electromyography (sEMG), as a non-invasive method, is crucial for monitoring muscle status. It is characterized by its real-time, portable nature and is extensively utilized in sports and rehabilitation sciences. This study proposed a wireless acquisition system based on multi-channel sEMG for objective monitoring of grip force. The system consists of an sEMG acquisition module containing four-channel discrete terminals and a host computer receiver module, using Bluetooth wireless transmission. The system is portable, wearable, low-cost, and easy to operate. Leveraging the system, an experiment for grip force prediction was designed, employing the bald eagle search (BES) algorithm to enhance the Random Forest (RF) algorithm. This approach established a grip force prediction model based on dual-channel sEMG signals. As tested, the performance of acquisition terminal proceeded as follows: the gain was up to 1125 times, and the common mode rejection ratio (CMRR) remained high in the sEMG signal band range (96.94 dB (100 Hz), 84.12 dB (500 Hz)), while the performance of the grip force prediction algorithm had an R2 of 0.9215, an MAE of 1.0637, and an MSE of 1.7479. The proposed system demonstrates excellent performance in real-time signal acquisition and grip force prediction, proving to be an effective muscle status monitoring tool for rehabilitation, training, disease condition surveillance and scientific fitness applications.

This review explores the historical and current significance of gestures as a universal form of communication with a focus on hand gestures in virtual reality applications. It highlights the evolution of gesture detection systems from the 1990s, which used computer algorithms to find patterns in static images, to the present day where advances in sensor technology, artificial intelligence, and computing power have enabled real-time gesture recognition. The paper emphasizes the role of hand gestures in virtual reality (VR), a field that creates immersive digital experiences through the Ma blending of 3D modeling, sound effects, and sensing technology. This review presents state-of-the-art hardware and software techniques used in hand gesture detection, primarily for VR applications. It discusses the challenges in hand gesture detection, classifies gestures as static and dynamic, and grades their detection difficulty. This paper also reviews the haptic devices used in VR and their advantages and challenges. It provides an overview of the process used in hand gesture acquisition, from inputs and pre-processing to pose detection, for both static and dynamic gestures.

BACKGROUND: Handgrip strength (HGS) is an indicator of muscular strength, used in the diagnosis of sarcopenia, undernutrition, and physical frailty as well as recovery. Typically, the maximum HGS value is used; however, recent evidence suggests the exploration of new indicators provided based on the force-time curve to achieve a more comprehensive assessment of muscle function. Therefore, the objective was to identify indicators of the HGS profile beyond maximum HGS, based on force-time curves, and to systematize knowledge about their applications to various types of samples, health issues, and physical performance.
METHODS: A systematic review was performed including studies whose participants\' HGS was assessed with a digital or adapted dynamometer. The outcome measures were HGS profile indicators calculated from the force-time curve.
RESULTS: a total of 15 studies were included, and the following indicators were identified: grip fatigue, fatigability index, fatigue rate, fatigue resistance, time to 80% maximal voluntary contraction, plateau coefficient of variability, time to maximum value, T-90%, release rate, power factor, grip work, average integrated area, endurance, cycle duration, time between cycles, maximum and minimum force-velocity, rate of grip force, final force, inflection point, integrated area, submaximal control, and response time.
CONCLUSIONS: Various indicators based on the force-time curve can be assessed through digital or adapted dynamometers. Future research should analyze these indicators to understand their implications for muscle function assessment, to standardize evaluation procedures, to identify clinically relevant measures, and to clarify their implications in clinical practice.

Carpal tunnel syndrome (CTS) is the most common cause of peripheral compressive neuropathy and consists of compression of the median nerve in the wrist. Although there are several etiologies, idiopathic is the most prevalent origin, and among the forms of treatment for CTS, conservative is the most indicated. However, despite the high prevalence in and impact of this syndrome on the healthcare system, there are still controversies regarding the best therapeutic approach for patients. Therefore, noting that some studies point to vitamin D deficiency as an independent risk factor, which increases the symptoms of the syndrome, this study evaluated the role of vitamin D supplementation and its influence on pain control, physical examination and response electroneuromyography to conservative treatment of carpal tunnel syndrome. For this, the sample consisted of 14 patients diagnosed with CTS and hypovitaminosis D, who were allocated into two groups. The control group received corticosteroid treatment, while the experimental group received corticosteroid treatment associated with vitamin D. Thus, from this study, it can be concluded that patients who received vitamin D, when compared to those who did not receive it, showed improvement in the degree of pain intensity, a reduction in symptom severity and an improvement in some electroneuromyographic parameters.

Endothelial dysfunction decreases exercise limb blood flow (BF) and muscle oxygenation. Acute L-Citrulline supplementation (CIT) improves muscle tissue oxygen saturation index (TSI) and deoxygenated hemoglobin (HHb) during exercise. Although CIT improves endothelial function (flow-mediated dilation [FMD]) in hypertensive women, the impact of CIT on exercise BF and muscle oxygenation (TSI) and extraction (HHb) are unknown. We examined the effects of CIT (10 g/day) and a placebo for 4 weeks on blood pressure (BP), arterial vasodilation (FMD, BF, and vascular conductance [VC]), and forearm muscle oxygenation (TSI and HHb) at rest and during exercise in 22 hypertensive postmenopausal women. Compared to the placebo, CIT significantly (p < 0.05) increased FMD (Δ-0.7 ± 0.6% vs. Δ1.6 ± 0.7%) and reduced aortic systolic BP (Δ3 ± 5 vs. Δ-4 ± 6 mmHg) at rest and improved exercise BF (Δ17 ± 12 vs. Δ48 ± 16 mL/min), VC (Δ-21 ± 9 vs. Δ41 ± 14 mL/mmHg/min), TSI (Δ-0.84 ± 0.58% vs. Δ1.61 ± 0.46%), and HHb (Δ1.03 ± 0.69 vs. Δ-2.76 ± 0.77 μM). Exercise BF and VC were positively correlated with improved FMD and TSI during exercise (all p < 0.05). CIT improved exercise artery vasodilation and muscle oxygenation via increased endothelial function in hypertensive postmenopausal women.

(1) Background: The assessment of muscle mass is crucial in the nutritional evaluation of patients with colorectal cancer (CRC), as decreased muscle mass is linked to increased complications and poorer prognosis. This study aims to evaluate the utility of AI-assisted L3 CT for assessing body composition and determining low muscle mass using both the Global Leadership Initiative on Malnutrition (GLIM) criteria for malnutrition and the European Working Group on Sarcopenia in Older People (EWGSOP2) criteria for sarcopenia in CRC patients prior to surgery. Additionally, we aim to establish cutoff points for muscle mass in men and women and propose their application in these diagnostic frameworks. (2) Methods: This retrospective observational study included CRC patients assessed by the Endocrinology and Nutrition services of the Regional University Hospitals of Malaga, Virgen de la Victoria of Malaga, and Vall d\'Hebrón of Barcelona from October 2018 to July 2023. A morphofunctional assessment, including anthropometry, bioimpedance analysis (BIA), and handgrip strength, was conducted to apply the GLIM criteria for malnutrition and the EWGSOP2 criteria for sarcopenia. Body composition evaluation was performed through AI-assisted analysis of CT images at the L3 level. ROC analysis was used to determine the predictive capacity of variables derived from the CT analysis regarding the diagnosis of low muscle mass and to describe cutoff points. (3) Results: A total of 586 patients were enrolled, with a mean age of 68.4 ± 10.2 years. Using the GLIM criteria, 245 patients (41.8%) were diagnosed with malnutrition. Applying the EWGSOP2 criteria, 56 patients (9.6%) were diagnosed with sarcopenia. ROC curve analysis for the skeletal muscle index (SMI) showed a strong discriminative capacity of muscle area to detect low fat-free mass index (FFMI) (AUC = 0.82, 95% CI 0.77-0.87, p < 0.001). The identified SMI cutoff for diagnosing low FFMI was 32.75 cm2/m2 (Sn 77%, Sp 64.3%; AUC = 0.79, 95% CI 0.70-0.87, p < 0.001) in women, and 39.9 cm2/m2 (Sn 77%, Sp 72.7%; AUC = 0.85, 95% CI 0.80-0.90, p < 0.001) in men. Additionally, skeletal muscle area (SMA) showed good discriminative capacity for detecting low appendicular skeletal muscle mass (ASMM) (AUC = 0.71, 95% CI 0.65-0.76, p < 0.001). The identified SMA cutoff points for diagnosing low ASMM were 83.2 cm2 (Sn 76.7%, Sp 55.3%; AUC = 0.77, 95% CI 0.69-0.84, p < 0.001) in women and 112.6 cm2 (Sn 82.3%, Sp 58.6%; AUC = 0.79, 95% CI 0.74-0.85, p < 0.001) in men. (4) Conclusions: AI-assisted body composition assessment using CT is a valuable tool in the morphofunctional evaluation of patients with colorectal cancer prior to surgery. CT provides quantitative data on muscle mass for the application of the GLIM criteria for malnutrition and the EWGSOP2 criteria for sarcopenia, with specific cutoff points established for diagnostic use.