Transcriptome profiling of fast/glycolytic and slow/oxidative muscle fibers in aging and obesity.

Aging and obesity pose significant threats to public health and are major contributors to muscle atrophy. The trends in muscle fiber types under these conditions and the transcriptional differences between different muscle fiber types remain unclear. Here, we demonstrate distinct responses of fast/glycolytic fibers and slow/oxidative fibers to aging and obesity. We found that in muscles dominated by oxidative fibers, the proportion of oxidative fibers remains unchanged during aging and obesity. However, in muscles dominated by glycolytic fibers, despite the low content of oxidative fibers, a significant decrease in proportion of oxidative fibers was observed. Consistently, our study uncovered that during aging and obesity, fast/glycolytic fibers specifically increased the expression of genes associated with muscle atrophy and inflammation, including Dkk3, Ccl8, Cxcl10, Cxcl13, Fbxo32, Depp1, and Chac1, while slow/oxidative fibers exhibit elevated expression of antioxidant protein Nqo-1 and downregulation of Tfrc. Additionally, we noted substantial differences in the expression of calcium-related signaling pathways between fast/glycolytic fibers and slow/oxidative fibers in response to aging and obesity. Treatment with a calcium channel inhibitor thapsigargin significantly increased the abundance of oxidative fibers. Our study provides additional evidence to support the transcriptomic differences in muscle fiber types under pathophysiological conditions, thereby establishing a theoretical basis for modulating muscle fiber types in disease treatment.

Nongenetic Precise Neuromodulation and Spatiotemporal Neuroprotection for Epilepsy Therapy via Rationally Designed Multifunctional Nanotransducer.

The precise modulation of electrical activity in specific neuronal populations is paramount for rectifying abnormal neurological functions and is a critical element in the therapeutic arsenal for neurological disorders. However, achieving a balance between minimal invasiveness and robust neuroprotection poses a considerable challenge. Herein, we present a nanoneuromodulation strategy integrating neuroprotective features to effectively address epilepsy with minimal invasiveness and enable wireless functionality. Strategically engineered nanotransducer, adorned with platinum (Pt) decoration with titanium disulfide (TiS2) (TiS2/Pt), enables precise modulation of neuronal electrical activity in vitro and in vivo, ensuring exceptional temporal fidelity under millisecond-precision near-infrared (NIR) light pulses irradiation. Concurrently, TiS2/Pt showcase a pronounced enhancement in enzyme-mimicking activity, offering a robust defense against oxidative neurological injury in vitro. Nanotransducer-enabled wireless neuromodulation with biocatalytic neuroprotective capacity is highly effective in alleviating epileptic high-frequency neural activity and diminishing oxidative stress levels, thereby restoring redox equilibrium. This integrated therapeutic approach reduces the severity of epilepsy, demonstrating minimal invasiveness and obviating the requirements for genetic manipulation and optical fiber implantation, while providing an alternative avenue for neurological disorder treatment.

Muscle attenuation, not skeletal muscle index, is an independent prognostic factor for survival in gastric cancer patients with overweight and obesity.

OBJECTIVES: Skeletal muscle index (SMI) is insufficient for evaluating muscle in obesity, and muscle attenuation (MA) may be a preferred indicator. This study aimed to investigate whether MA has greater prognostic value than SMI in gastric cancer patients with overweight and obesity. METHODS: Clinical parameters of 1312 patients with gastric cancer who underwent radical gastrectomy were prospectively collected between 2013 and 2019. MA and SMI were analyzed by computed tomography scan. Overweight/obesity was defined as body mass index (BMI) ≥24 kg/m2. The hazard ratio (HR) for death was calculated using Cox regression analysis. RESULTS: Among all patients, 405 were identified as overweight and obese, and 907 were identified as normal and underweight. MA was inversely associated with BMI and visceral fat area. Among the 405 patients with overweight and obesity, 212 patients (52%) were diagnosed with low MA. In the overweight/obese group, MA was an independent predictor for overall survival (HR, 1.610; P = 0.021) in multivariate Cox regression analyses, whereas SMI did not remain in the model. In the normal/underweight group, both low MA (HR, 1.283; P = 0.039) and low SMI (HR, 1.369; P = 0.008) were independent factors of overall survival. Additionally, 318 patients were identified as having visceral obesity in the overweight/obese group, and low MA was also an independent prognostic factor for survival in these patients (HR, 1.765; P = 0.013). CONCLUSION: MA had a higher prognostic value than SMI in overweight and obese patients with gastric cancer after radical gastrectomy.

Black Phosphorus Flake-Enabled Wireless Neuromodulation for Epilepsy Treatment.

Epilepsy is a prevalent and severe neurological disorder and generally requires prolonged electrode implantation and tether brain stimulation in refractory cases. However, implants may cause potential chronic immune inflammation and permanent tissue damage due to material property mismatches with soft brain tissue. Here, we demonstrated a nanomaterial-enabled near-infrared (NIR) neuromodulation approach to provide nongenetic and nonimplantable therapeutic benefits in epilepsy mouse models. Our study showed that crystal-exfoliated photothermal black phosphorus (BP) flakes could enhance neural activity by altering the membrane capacitive currents in hippocampus neurons through NIR photothermal neuromodulation. Optical stimulation facilitated by BP flakes in hippocampal slices evoked action potentials with a high spatiotemporal resolution. Furthermore, BP flake-enabled NIR neuromodulation of hippocampus neural circuits can suppress epileptic signals in epilepsy model mice with minimal invasiveness and high biocompatibility. Consequently, nanomaterial-enabled NIR neuromodulation may open up opportunities for nonimplantable optical therapy of epilepsy in nontransgenic organisms.

Establishment and validation of novel nomograms to predict muscle quality in colorectal cancer patients.

OBJECTIVES: The skeletal muscle mass index and skeletal muscle radiodensity have promise as specific diagnostic indicators for muscle quality. However, the difficulties in measuring low skeletal muscle mass index and low skeletal muscle radiodensity limit their use in routine clinical practice, impeding early screening and diagnosis. The objective of this study is to develop a nomogram that incorporates preoperative factors for predicting low skeletal muscle mass index and low skeletal muscle radiodensity. METHODS: A total of 1692 colorectal cancer patients between 2015 and 2021 were included. The patients were randomly divided into a training cohort (n = 1353) and a validation cohort (n = 339). Nomogram models were calibrated using the area under the curve, calibration curves, and the Hosmer-Lemeshow test to assess their predictive ability. Finally, a decision curve was applied to assess the clinical usefulness. RESULTS: In a prediction model for low skeletal muscle mass index, age, body mass index, and grip strength were incorporated as variables. For low skeletal muscle radiodensity, age, sex, body mass index, serum hemoglobin level, and grip strength were included as predictors. In the training cohort, the area under the curve value for low skeletal muscle mass index was 0.750 (95% CI, 0.726-0.773), whereas for low skeletal muscle radiodensity, it was 0.763 (95% CI, 0.739-0.785). The Hosmer-Lemeshow test confirmed that both models fit well in both cohorts. Decision curve analysis was applied to assess the clinical usefulness of the model. CONCLUSIONS: The incorporation of preoperative factors into the nomogram-based prediction model represents a significant advancement in the muscle quality assessment. Its implementation has the potential to early screen patients at risk of low skeletal muscle mass index and low skeletal muscle radiodensity.

Discovery of distinct cancer cachexia phenotypes using an unsupervised machine-learning algorithm.

OBJECTIVES: Cancer cachexia is a debilitating condition with widespread negative effects. The heterogeneity of clinical features within patients with cancer cachexia is unclear. The identification and prognostic analysis of diverse phenotypes of cancer cachexia may help develop individualized interventions to improve outcomes for vulnerable populations. The aim of this study was to show that the machine learning-based cancer cachexia classification model generalized well on the external validation cohort. METHODS: This was a nationwide multicenter observational study conducted from October 2012 to April 2021 in China. Unsupervised consensus clustering analysis was applied based on demographic, anthropometric, nutritional, oncological, and quality-of-life data. Key characteristics of each cluster were identified using the standardized mean difference. We used logistic and Cox regression analysis to evaluate 1-, 3-, 5-y, and overall mortality. RESULTS: A consensus clustering algorithm was performed for 4329 patients with cancer cachexia in the discovery cohort, and four clusters with distinct phenotypes were uncovered. From clusters 1 to 4, the clinical characteristics of patients showed a transition from almost unimpaired to mildly, moderately, and severely impaired. Consistently, an increase in mortality from clusters 1 to 4 was observed. The overall mortality rate was 32%, 40%, 54%, and 68%, and the median overall survival time was 21.9, 18, 16.7, and 13.6 mo for patients in clusters 1 to 4, respectively. Our machine learning-based model performed better in predicting mortality than the traditional model. External validation confirmed the above results. CONCLUSIONS: Machine learning is valuable for phenotype classifications of patients with cancer cachexia. Detection of clinically distinct clusters among cachexic patients assists in scheduling personalized treatment strategies and in patient selection for clinical trials.

Sarcopenia and malignancies: epidemiology, clinical classification and implications.

Sarcopenia is a progressive systemic skeletal muscle disorder characterized by a pathological decline in muscle strength, quantity, and quality, which frequently affects the elderly population. The majority of cancer patients are of advanced age. Patients may already have sarcopenia prior to cancer development, and those with cancer are prone to developing sarcopenia due to hypercatabolism, inflammation, reduced physical fitness, anorexia, adverse effects, and stress associated with anticancer therapy. Based on the timing, sarcopenia in patients with cancer can be categorized into three: pre-existing sarcopenia before the onset of cancer, sarcopenia related to cancer, and sarcopenia related to cancer treatment. Sarcopenia not only changes the body composition of patients with cancer but also increases the incidence of postoperative complications, reduces therapeutic efficacy, impairs quality of life, and results in shortened survival. Different therapeutic strategies are required to match the cancer status and physical condition of patients with different etiologies and stages of sarcopenia. Here, we present a comprehensive review of the epidemiology and diagnosis of sarcopenia in patients with cancer, elucidate the complex interactions between cancer and sarcopenia, and provide evidence-based strategies for sarcopenia management in these patients.

Prediction for recurrent non-muscle invasive bladder cancer.

Non-muscle invasive bladder cancer (NMIBC) has a high recurrence rate, which places a significant burden on both patients and the healthcare system. Hence, it holds significant importance to predict the recurrence risk following treatment for individuals diagnosed with non-muscle invasive bladder cancer (NMIBC). As new generation technologies continue to emerge, an increasing number of recurrence risk prediction tools are being developed and discovered. This article provides an overview of the primary recurrence risk prediction tools currently available, including the liquid biopsy, tissue biopsy, and risk prediction tables. Each of these tools is described in detail and illustrated with relevant examples. Furthermore, we conduct an analysis of the advantages and disadvantages of these tools. This article aims to enhance the reader's understanding of the current progress in recurrence prediction tools and encourage their practical utilization in the fields of precision medicine and public health.

Transcranial Nongenetic Neuromodulation via Bioinspired Vesicle-Enabled Precise NIR-II Optical Stimulation.

Regulating the activity of specific neurons is essentially important in neurocircuit dissection and neuropathy therapy. As a recently developed strategy, nanomaterial-enabled nongenetic neuromodulations that realize remote physical stimuli have made vast progress and shown great clinical potential. However, minimal invasiveness and high spatiotemporal resolution are still challenging for nongenetic neuromodulation. Herein, a second near-infrared (NIR-II)-light-induced transcranial nongenetic neurostimulation via bioinspired nanovesicles is reported. The rationally designed vesicles are obtained from vesicle-membrane-confined enzymatic reactions. This study demonstrates that the vesicle-enabled NIR-II photothermal stimuli can elicit neuronal signaling dynamics with precise spatiotemporal control and thus evoke defined neural circuits in nontransgenic mice. Moreover, the vesicle-mediated NIR-II optical stimulation can regulate mouse motor behaviors with minimal invasiveness by eliminating light-emitting implants. Furthermore, the biological modulation is integrated with photoacoustic brain imaging, realizing navigational, and efficient neuromodulation. Such transcranial and precise NIR-II optical neuromodulation mediated by bioinspired vesicles shows the potential for the optical-theranostics of neurological diseases in nontransgenic organisms.

The novel pickering emulsion gels stabilized by zein hydrolysate-chitin nanocrystals coacervates: Improvement on stability and bioaccessibility for curcumin.

The aim of this paper was to explore the synergistic mechanism of the novel Pickering emulsion gels stabilized by zein hydrolysate (ZH, low DH of 5%)-chitin nanocrystals (CNCs) coacervates, and investigate their improvement on the stability and bioaccessibility of curcumin. Interestingly, the ZH with low DH of 5% exhibited aggregated precipitation at pH 5.0. The ZH was absorbed on the surface of CNCs to form ZH-CNCs coacervates by hydrogen bonding and electrostatic neutralization. Moreover, the novel Pickering emulsion gels stabilized by the appropriate ZH-CNCs coacervates showed better rheologicalproperties, emulsion stability and oxidation resistance. As new carriers for curcumin, they could effectively improve the stability and antioxidantactivity (over 90%). Further, the free fatty acid (FFA) release ratewas reduced to below 3.89% and the corresponding bioaccessibility increased to over 80% in vitro digestion. The novel delivery system was potentially designed in foods and pharmaceuticals for the purposes of enhanced stability, delayed lipolysis, or sustained nutrient release.