Light pollution: time to consider testicular effects.

Technological advances have led to a modern-day lighting and smartphone revolution, with artificial light exposure at night increasing to levels never before seen in the evolutionary history of living systems on Earth. Light as a pollutant, however, remains largely unrecognized, and the reproductive effects of light pollution are mostly if not entirely unconsidered. This is despite the reproductive system being intricately linked to metabolism and the circadian system, both of which can be disturbed even by low levels of light. Here, we aim to change this perspective by reviewing the physiological and pathophysiological mechanisms by which light exposure alters the intricate hormonal, metabolic and reproductive networks that are relevant to reproductive toxicology. Nascent human studies have recently identified the photoreceptors responsible for the light dose relationship with melatonin suppression and circadian re-entrainment, directly shown the association between the alignment of light-dark cycles with activity-rest cycles on metabolic health and provided proof-of-principle that properly timed blue light-enriched and blue light-depleted delivery can accelerate circadian re-entrainment. With these advances, there is now a need to consider testicular effects of light pollution.

Prospective Human Validation of Artificial Intelligence Interventions in Cardiology: A Scoping Review.

Background: Despite the potential of artificial intelligence (AI) in enhancing cardiovascular care, its integration into clinical practice is limited by a lack of evidence on its effectiveness with respect to human experts or gold standard practices in real-world settings. Objectives: The purpose of this study was to identify AI interventions in cardiology that have been prospectively validated against human expert benchmarks or gold standard practices, assessing their effectiveness, and identifying future research areas. Methods: We systematically reviewed Scopus and MEDLINE to identify peer-reviewed publications that involved prospective human validation of AI-based interventions in cardiology from January 2015 to December 2023. Results: Of 2,351 initial records, 64 studies were included. Among these studies, 59 (92.2%) were published after 2020. A total of 11 (17.2%) randomized controlled trials were published. AI interventions in 44 articles (68.75%) reported definite clinical or operational improvements over human experts. These interventions were mostly used in imaging (n = 14, 21.9%), ejection fraction (n = 10, 15.6%), arrhythmia (n = 9, 14.1%), and coronary artery disease (n = 12, 18.8%) application areas. Convolutional neural networks were the most common predictive model (n = 44, 69%), and images were the most used data type (n = 38, 54.3%). Only 22 (34.4%) studies made their models or data accessible. Conclusions: This review identifies the potential of AI in cardiology, with models often performing equally well as human counterparts for specific and clearly scoped tasks suitable for such models. Nonetheless, the limited number of randomized controlled trials emphasizes the need for continued validation, especially in real-world settings that closely examine joint human AI decision-making.

Steroid Hormone Biosynthesis and Dietary Related Metabolites Associated with Excessive Daytime Sleepiness.

Background: Excessive daytime sleepiness (EDS) is a complex sleep problem that affects approximately 33% of the United States population. Although EDS usually occurs in conjunction with insufficient sleep, and other sleep and circadian disorders, recent studies have shown unique genetic markers and metabolic pathways underlying EDS. Here, we aimed to further elucidate the biological profile of EDS using large scale single- and pathway-level metabolomics analyses. Methods: Metabolomics data were available for 877 metabolites in 6,071 individuals from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) and EDS was assessed using the Epworth Sleepiness Scale (ESS) questionnaire. We performed linear regression for each metabolite on continuous ESS, adjusting for demographic, lifestyle, and physiological confounders, and in sex specific groups. Subsequently, gaussian graphical modelling was performed coupled with pathway and enrichment analyses to generate a holistic interactive network of the metabolomic profile of EDS associations. Findings: We identified seven metabolites belonging to steroids, sphingomyelin, and long chain fatty acids sub-pathways in the primary model associated with EDS, and an additional three metabolites in the male-specific analysis. The identified metabolites particularly played a role in steroid hormone biosynthesis. Interpretation: Our findings indicate that an EDS metabolomic profile is characterized by endogenous and dietary metabolites within the steroid hormone biosynthesis pathway, with some pathways that differ by sex. Our findings identify potential pathways to target for addressing the causes or consequences of EDS and related sleep disorders. Funding: Details regarding funding supporting this work and all studies involved are provided in the acknowledgments section.

Timing of sodium-glucose cotransporter 2 inhibitor initiation and post-discharge outcomes in acute heart failure with diabetes: A population-based cohort study.

AIMS: Results from randomized trials suggest benefit of sodium-glucose cotransporter 2 (SGLT2) inhibitor initiation in clinically stable acute heart failure. We aim to examine the real-world effectiveness of early versus delayed post-discharge SGLT2 inhibitor initiation in people with acute heart failure and type 2 diabetes. METHODS AND RESULTS: Using linkable administrative databases in Ontario, Canada, individuals aged 66 years or older with type 2 diabetes who were discharged to the community from acute care hospitals for heart failure between 1 July 2016 and 31 March 2020 were included in this retrospective, population-based cohort study. The primary outcome was hospitalization for heart failure (HHF) or cardiovascular mortality as a composite. Follow-up started from discharge for maximum 1 year. We compared outcomes between post-discharge SGLT2 inhibitor initiation within 3 days, 4-90 days, or 91-180 days, versus delayed initiation for at least 180 days. The 'clone-censor-weight' approach with a target trial emulation framework was used to address time-related biases. There were 9641 eligible individuals. After cloning and artificial censoring, there were 38 564 clones, 12 439 person-years, and 7584 events. Compared to delayed initiation for at least 180 days, initiation within 3 days post-discharge was associated with a lower 1-year risk of HHF or cardiovascular mortality (risk ratio [RR] 0.65, 95% confidence interval [CI] 0.45-0.83), while initiation 4-90 days (RR 0.83, 95% CI 0.72-0.93) or 91-180 days (RR 0.89, 95% CI 0.79-0.97) showed smaller risk reduction. CONCLUSION: Real-world evidence supports early SGLT2 inhibitor initiation to reduce HHF or cardiovascular mortality in acute heart failure and type 2 diabetes.

Analysis of C-reactive protein omics-measures associates methylation risk score with sleep health and related health outcomes.

Introduction: DNA methylation (DNAm) predictors of high sensitivity C-reactive protein (CRP) offer a stable and accurate means of assessing chronic inflammation, bypassing the CRP protein fluctuations secondary to acute illness. Poor sleep health is associated with elevated inflammation (including elevated blood CRP levels) which may explain associations of sleep insufficiency with metabolic, cardiovascular and neurological diseases. Our study aims to characterize the relationships among sleep health phenotypes and CRP markers -blood, genetic, and epigenetic indicators-within the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Methods: In HCHS/SOL, methylation risk scores (MRS)-CRP and polygenetic risk score (PRS)-CRP were constructed separately as weighted sums of methylation beta values or allele counts, respectively, for each individual. Sleep health phenotypes were measured using self-reported questionnaires and objective measurements. Survey-weighted linear regression established the association between the multiple sleep phenotypes (obstructive sleep apnea (OSA), sleep duration, insomnia and excessive sleepiness symptom), cognitive assessments, diabetes and hypertension with CRP markers while adjusting for age, sex, BMI, study center, and the first five principal components of genetic ancestry in HCHS/SOL. Results: We included 2221 HCHS/SOL participants (age range 37-76 yrs, 65.7% female) in the analysis. Both the MRS-CRP (95% confidence interval (CI): 0.32-0.42, p = 3.3 × 10-38) and the PRS-CRP (95% CI: 0.15-0.25, p = 1 × 10-14) were associated with blood CRP level. Moreover, MRS-CRP was associated with sleep health phenotypes (OSA, long sleep duration) and related conditions (diabetes and hypertension), while PRS-CRP markers were not associated with these traits. Circulating CRP level was associated with sleep duration and diabetes. Associations between OSA traits and metabolic comorbidities weakened after adjusting for MRS-CRP, most strongly for diabetes, and least for hypertension. Conclusions: MRS-CRP is a promising estimate for systemic and chronic inflammation as reflected by circulating CRP levels, which either mediates or serves as a common cause of the association between sleep phenotypes and related comorbidities, especially in the presence of diabetes.

A sociodemographic index identifies sex-related effects on insomnia in the Hispanic Community Health Study/Study of Latinos.

Study Objectives: Sex differences are related to both biological factors and the gendered environment. We constructed measures to model sex-related differences beyond binary sex. Methods: Data came from the baseline visit of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). We applied the least absolute shrinkage and selection operator penalized logistic regression of male versus female sex over sociodemographic, acculturation, and psychological factors jointly. Two "gendered indices," the gendered index of sociodemographic environment (GISE) and gendered index of psychological and sociodemographic environment, summarizing the sociodemographic environment (GISE) and psychosocial and sociodemographic environment (GIPSE) associated with sex, were calculated by summing these variables, weighted by their regression coefficients. We examined the association of these indices with insomnia, a phenotype with strong sex differences, in sex-adjusted and sex-stratified analyses. Results: The distribution of GISE and GIPSE differed by sex with higher values in male individuals. In an association model with insomnia, male sex was associated with a lower likelihood of insomnia (odds ratio [OR] = 0.60, 95% CI [0.53, 0.67]). Including GISE in the model, the association was slightly weaker (OR = 0.63, 95% CI [0.56, 0.70]), and weaker when including instead GIPSE in the association model (OR = 0.78, 95% CI [0.69, 0.88]). Higher values of GISE and of GIPSE, more common in the male sex, were associated with a lower likelihood of insomnia, in analyses adjusted for sex (per 1 standard deviation of the index, GISE OR = 0.92, 95% CI [0.87, 0.99], GIPSE OR = 0.65, 95% CI [0.61, 0.70]). Conclusions: New measures such as GISE and GIPSE capture sex-related differences beyond binary sex and have the potential to better model and inform research studies of sleep health.

Cardiovascular phenotypes in type 2 diabetes: Latent class analysis of the CANVAS Program and CREDENCE trial.

AIM: To identify unique clinical phenotypes in type 2 diabetes (T2D) and investigate their treatment response to canagliflozin using latent class analysis. METHODS: This was a pooled latent class analysis of the individuals in the CANVAS Program and CREDENCE trial. The co-primary endpoints were hospitalization for heart failure (HHF) and the composite of cardiovascular death (CVD) or HHF. Secondary endpoints included three-point major adverse CV events, its individual components, and all-cause mortality. We completed Cox proportional hazards models to evaluate the effect of canagliflozin across phenotypes. RESULTS: Four distinct phenotypes were identified: Phenotype 1 (n = 966, 6.6%), with the lowest prevalence of heart failure, kidney dysfunction and hypertension; Phenotype 2 (n = 4169, 28.7%), primarily comprising females with a high prevalence of atherosclerotic vascular disease (ASCVD); Phenotype 3 (n = 7108, 48.9%), predominately males with a high prevalence of ASCVD; and Phenotype 4 (n = 2300, 15.8%), possessing the highest prevalences of HF and renal dysfunction. A hierarchical increase in the risk of the primary endpoint was observed across the phenotypes, with the highest CV risk observed for Phenotype 4 (hazard ratio for HHF: 7.57 [95% CI: 4.19-13.69]). Canagliflozin significantly reduced HHF and the composite CVD or HHF across phenotypes (all P values for interaction > .05). CONCLUSION: We identified four clinically distinct T2D phenotypes with differential CV risks. Canagliflozin reduced the risk of CV events, irrespective of the phenotype, emphasizing its broad therapeutic acceptability.

Deterministic Fabrication of Liquid Metal Nanopatterns for Nanophotonics Applications.

Gallium-based liquid metals (LMs) are widely used for stretchable and reconfigurable electronics thanks to their fluidic nature and excellent conductivity. These LMs possess attractive optical properties for photonics applications as well. However, due to the high surface tension of the LMs, it is challenging to form LM nanostructures with arbitrary shapes using conventional nanofabrication techniques. As a result, LM-based nanophotonics has not been extensively explored. Here, a simple yet effective technique is demonstrated to deterministically fabricate LM nanopatterns with high yield over a large area. This technique demonstrates for the first time the capability to fabricate LM nanophotonic structures of various precisely defined shapes and sizes using two different LMs, that is, liquid gallium and liquid eutectic gallium-indium alloy. High-density arrays of LM nanopatterns with critical feature sizes down to ≈100 nm and inter-pattern spacings down to ≈100 nm are achieved, corresponding to the highest resolution of any LM fabrication technique developed to date. Additionally, the LM nanopatterns demonstrate excellent long-term stability under ambient conditions. This work paves the way toward further development of a wide range of LM nanophotonics technologies and applications.

Point Cloud Registration in Laparoscopic Liver Surgery Using Keypoint Correspondence Registration Network.

Laparoscopic liver surgery is a newly developed minimally invasive technique and represents an inevitable trend in the future development of surgical methods. By using augmented reality (AR) technology to overlay preoperative CT models with intraoperative laparoscopic videos, surgeons can accurately locate blood vessels and tumors, significantly enhancing the safety and precision of surgeries. Point cloud registration technology is key to achieving this effect. However, there are two major challenges in registering the CT model with the point cloud surface reconstructed from intraoperative laparoscopy. First, the surface features of the organ are not prominent. Second, due to the limited field of view of the laparoscope, the reconstructed surface typically represents only a very small portion of the entire organ. To address these issues, this paper proposes the keypoint correspondence registration network (KCR-Net). This network first uses the neighborhood feature fusion module (NFFM) to aggregate and interact features from different regions and structures within a pair of point clouds to obtain comprehensive feature representations. Then, through correspondence generation, it directly generates keypoints and their corresponding weights, with keypoints located in the common structures of the point clouds to be registered, and corresponding weights learned automatically by the network. This approach enables accurate point cloud registration even under conditions of extremely low overlap. Experiments conducted on the ModelNet40, 3Dircadb, DePoLL demonstrate that our method achieves excellent registration accuracy and is capable of meeting the requirements of real-world scenarios.

The Continuing Scourge of Atherosclerotic Cardiovascular Disease: Importance of Multidisciplinary and Innovative Person-Centred Approaches.

This article discusses the complex approach to managing atherosclerotic cardiovascular disease (ASCVD), focusing on person-centred care (PCC) to align treatment strategies with individual patient narratives, values, and preferences. It identifies significant challenges in management of ASCVD, such as the necessity for multidisciplinary strategies and the need for enhanced patient care, particularly given the coexistence of ASCVD with other cardiometabolic risk factors. The paper points out existing practice gaps, including limited patient-provider information sharing and decision making, and considers the role of technology in personalizing care and improving outcomes. Strategies such as electronic health records, telehealth platforms, and motivational interviewing are examined for their potential to boost patient engagement and adherence to treatment. In addition, the article discusses systemic issues such as health care provider burnout and the importance of creating customized care plans for patients with multiple health conditions. The integration of varied approaches, including the involvement of community pharmacists and health coaches, is suggested as important for effective management of ASCVD. This review highlights the need for an innovative, holistic strategy for management of ASCVD and advocates for a transformative shift toward PCC that integrates individual, community, and system-level interventions to enhance patient engagement, therapy adherence, and overall outcomes.

The Peritoneum: Anatomy, Pathologic Findings, and Patterns of Disease Spread.

Disease spread in the abdomen and pelvis generally occurs in a predictable pattern in relation to anatomic landmarks and fascial planes. Anatomically, the abdominopelvic cavity is subdivided into several smaller spaces or compartments by key ligaments and fascial planes. The abdominal cavity has been traditionally divided into peritoneal, retroperitoneal, and pelvic extraperitoneal spaces. Recently, more clinically relevant classifications have evolved. Many pathologic conditions affect the abdominal cavity, including traumatic, inflammatory, infectious, and neoplastic processes. These abnormalities can extend beyond their sites of origin through various pathways. Identifying the origin of a disease process is the first step in formulating a differential diagnosis and ultimately reaching a final diagnosis. Pathologic conditions differ in terms of pathways of disease spread. For example, simple fluid tracks along fascial planes, respecting anatomic boundaries, while fluid from acute necrotizing pancreatitis can destroy fascial planes, resulting in transfascial spread without regard for anatomic landmarks. Furthermore, neoplastic processes can spread through multiple pathways, with a propensity for spread to noncontiguous sites. When the origin of a disease process is not readily apparent, recognizing the spread pattern can allow the radiologist to work backward and ultimately arrive at the site or source of pathogenesis. As such, a cohesive understanding of the peritoneal anatomy, the typical organ or site of origin for a disease process, and the corresponding pattern of disease spread is critical not only for initial diagnosis but also for establishing a road map for staging, anticipating further disease spread, guiding search patterns and report checklists, determining prognosis, and tailoring appropriate follow-up imaging studies. ©RSNA, 2024 Supplemental material is available for this article.

Simulating blood accumulation with improved smoothed particle hydrodynamics in surgical simulation system.

BACKGROUND: Blood accumulation often occurs during bleeding in surgery. Simulating the blood accumulation in surgical simulation system not only enhances the realism and immersion of surgical training, but also helps researchers better understand the physical properties of blood flow. METHODS: To realistically simulate the blood accumulation during the bleeding, this paper proposes a novel kernel function with non-negative second derivatives to improve the SPH method. Meanwhile, a simple form of boundary force equation is constructed to impose the solid boundary condition. RESULTS: We simulate the blood accumulation during liver bleeding and vessel bleeding respectively in the surgical simulation system. The simulation results show that there is no occurrence of blood physically penetrating the boundary. CONCLUSIONS: Applying the solid boundary condition to the blood by using the method proposed in this paper is not only convenient but can also eliminate compression instability in the blood accumulation simulation.

A new model of electrosurgical tissue damage for neurosurgery simulation.

BACKGROUND: Bipolar hemostasis electrocoagulation is a fundamental procedure in neurosurgery. A precise electrocoagulation model is essential to enable realistic visual feedback in virtual neurosurgical simulation. However, existing models lack an accurate description of the heat damage and irreversible tissue deformation caused by electrocoagulation, thus diminishing the visual realism. This work focuses on the electrocoagulation model for neurosurgery simulation. METHOD: In this paper, a position-based dynamics (PBD) model with a bioheat transfer and damage prediction (BHTDP) method is developed for simulating the deformation of brain tissue caused by electrocoagulation. The presented BTHDP method uses the Arrhenius equation to predict thermal damage of brain tissue. A deformation model with energy and thermal damage constraints is developed to characterize soft tissue deformation during heat absorption before and after thermal injury. Visual effect of damaged brain tissue is re-rendered. RESULT: To evaluate the accuracy of the proposed method, numerical simulations were conducted and compared with commercial finite element software. The maximum normalized error of the proposed model for predicting midpoint temperature is 10.3 % and the maximum error for predicting the thermal damage is 5.4 %. The contraction effects of heat-exposed anisotropic tissues are also simulated. The results indicate that the presented electrocoagulation model provides stable and realistic visual effects, making it applicable for simulating the electrocoagulation process in virtual neurosurgery.

Impact of cannabidiol on myocardial recovery in patients with acute myocarditis: Rationale & design of the ARCHER trial.

AIMS: Acute myocarditis, although a rare disease, can be associated with sudden cardiac death or the need for transplantation in both children and young adults. To date, there is no definitive evidence to support the routine use of immunosuppressive therapy or treatment targeting inflammation in patients with myocarditis. Animal models of cardiovascular (CV), as well as neurological diseases, have demonstrated that cannabidiol has significant anti-inflammatory properties and may represent a promising therapy in acute myocarditis. This efficacy has been shown in a murine model of autoimmune myocarditis as well as in in vitro and in vivo models of heart failure (HF). METHODS AND RESULTS: We present the rationale and design of the ARCHER Trial, an international multicentre, double-blind, randomized, placebo-controlled, phase II study examining the safety and efficacy of a pharmaceutically produced cannabidiol formulation, in patients with mild to moderate acute myocarditis. Eligible patients are those with acute myocarditis, randomized within 10 days of the diagnostic cardiac MRI (CMR), which has met defined diagnostic criteria for myocarditis. Oral treatment (cannabidiol or placebo) is titrated from 2.5 mg/kg of body weight up to 10 mg/kg of body weight b.i.d. (or highest tolerated dose) and taken for 12 weeks in addition to standard of care therapy for HF. The primary endpoints are defined as changes in global longitudinal strain (GLS) and extra cellular volume (ECV), measured by CMR at 12 weeks. Assuming 80% power, a 5% alpha risk and 25% missing CMR follow-up data at Week 12, 100 patients are required to demonstrate the desired treatment effect of 18%. The change in left ventricular ejection fraction (LVEF) from baseline to Week 12 was selected as the secondary endpoint. Additional exploratory endpoints include changes in hs-troponin, NT-proBNP, markers of inflammation and endothelial function during the 12-week treatment period. The trial is ongoing but is now more than 50% recruited. As enrolment in the trial continues, no interim data are available for inclusion in this Design paper. CONCLUSIONS: The ongoing ARCHER Trial is an international, multicentre, double-blind, randomized, placebo-controlled phase II study, designed to determine the effect of a pharmaceutically produced cannabidiol formulation on CMR parameters in patients presenting with acute myocarditis. Enrolment of 100 patients is expected to conclude in Q3 2024. Study results will be available in early 2025.

Use of Sodium-Glucose Co-Transporter 2 Inhibitors in Patients With Type 2 Diabetes and the Incidence of Retinal Vein Occlusion in Taiwan.

Purpose: The purpose of this study was to evaluate the risk of newly diagnosed retinal vein occlusion (RVO) in patients with type 2 diabetes (T2D) using sodium-glucose cotransporter-2 inhibitors (SGLT-2i) compared to dipeptidyl peptidase-4 inhibitors (DPP-4i). Methods: Claims data from the National Health Insurance Research Database of Taiwan were used in this nationwide retrospective cohort study. A target trial emulation framework was applied. Patients with T2D with no prior diagnosis of RVO who had newly commenced treatment with SGLT-2i or DPP-4i between May 1, 2016, and December 31, 2020, were included. Potential systematic differences in baseline characteristics between the paired groups were controlled using stabilized inverse probability of treatment weighting. The outcome of interest was incident RVO. The hazard ratio (HR) for SGLT-2i compared with that of DPP-4i was estimated using a Cox regression model. Results: Data from 123,567 and 578,665 patients receiving SGLT-2i and DPP-4i, respectively, were analyzed. The incidence of RVO was lower in patients newly receiving SGLT-2i (0.59 events per 1000 person-years) compared to those receiving DPP-4i (0.77 events per 1000 person-years) over a mean follow-up of 1.61 years. SGLT-2i users had a significantly lower risk of developing RVO compared with DPP-4i users (HR = 0.76, 95% confidence interval [CI] = 0.59-0.98). In the individual outcome analysis, SGLT-2i use was significantly associated with a lower risk of branch RVO (HR = 0.71, 95% CI = 0.52-0.96), but not central RVO (HR = 0.84, 95% CI = 0.57-1.24). Conclusions: The risk of developing RVO was lower in patients with T2D receiving SGLT-2i compared with that in those receiving DPP-4i.

Combining descriptive and predictive modeling to systematically design depth filtration-based harvest processes for biologics.

Advances in upstream production of biologics-particularly intensified fed-batch processes beyond 10% cell solids-have severely strained harvest operations, especially depth filtration. Bioreactors containing high amounts of cell debris (more than 40% particles <10 µm in diameter) are increasingly common and drive the need for more robust depth filtration processes, while accelerated timelines emphasize the need for predictive tools to accelerate development. Both needs are constrained by the current limited mechanistic understanding of the harvest filter-feedstream system. Historically, process development relied on screening scale-down depth filter devices and conditions to define throughput before fouling, indicated by increasing differential pressure and/or particle breakthrough (measured via turbidity). This approach is straightforward, but resource-intensive, and its results are inherently limited by the variability of the feedstream. Semi-empirical models have been developed from first principles to describe various mechanisms of filter fouling, that is, pore constriction, pore blocking, and/or surface deposit. Fitting these models to experimental data can assist in identifying the dominant fouling mechanism. Still, this approach sees limited application to guide process development, as it is descriptive, not predictive. To address this gap, we developed a hybrid modeling approach. Leveraging historical bench scale filtration process data, we built a partial least squares regression model to predict particle breakthrough from filter and feedstream attributes, and leveraged the model to demonstrate prediction of filter performance a priori. The fouling models are used to interpret and provide physical meaning to these computational models. This hybrid approach-combining the mechanistic insights of fouling models and the predictive capability of computational models-was used to establish a robust platform strategy for depth filtration of Chinese hamster ovary cell cultures. As new data continues to teach the computational models, in silico tools will become an essential part of harvest process development by enabling prospective experimental design, reducing total experimental load, and accelerating development under strict timelines.

The global clinical studies of long COVID.

People with long COVID are those who still have symptoms, signs, and conditions after the initial phase of infection of SARS-CoV-2. The incidence of long COVID varies among regions-31% in North America, 44% in Europe, and 51% in Asia, which is challenging the healthcare system, but there is limited guidelines for its treatment. With more and more nationwide projects funded by the government such as the RECOVER initiative in the United States and National Institute for Health Research funding in the United Kingdom, an increasing number of ongoing clinical trials are investigating the efficacy of diverse therapies on reversing long COVID. After searching the World Health Organization International Clinical Trial Registry Platform, 587 clinical studies are identified as long COVID studies. Among these, 312 studies (53.2%) are testing potential therapies. Most of the long COVID trials were conducted in the United States (58 trials [18.6%]), followed by India (55 trials [17.6%]), and Spain (20 trials [6.4%]). Interventions in these clinical trials include physical exercise, rehabilitation therapy, behavioral therapy, and pharmacological therapies including herbs, paxlovid, and fluvoxamine. These trials are aiming to deal with these long COVID symptoms and signs including fatigue, decreased pulmonary function, reduced cognitive function, and others. To date, only 11 of these 312 studies have published their results that were not confirmative, unfortunately. Future studies should be designed to address sleep disorders which were seldomly included in registered clinical studies. Moreover, interventions aimed at treating the underlying pathophysiology of long COVID are also necessary but currently lacking.