A regionally tailored epidemiological forecast and monitoring program to guide a healthcare system in the COVID-19 pandemic.

BACKGROUND: During the COVID-19 pandemic, analytics and predictive models built on regional data provided timely, accurate monitoring of epidemiological behavior, informing critical planning and decision-making for health system leaders. At Atrium Health, a large, integrated healthcare system in the southeastern United States, a team of statisticians and physicians created a comprehensive forecast and monitoring program that leveraged an array of statistical methods. METHODS: The program utilized the following methodological approaches: (i) exploratory graphics, including time plots of epidemiological metrics with smoothers; (ii) infection prevalence forecasting using a Bayesian epidemiological model with time-varying infection rate; (iii) doubling and halving times computed using changepoints in local linear trend; (iv) death monitoring using combination forecasting with an ensemble of models; (v) effective reproduction number estimation with a Bayesian approach; (vi) COVID-19 patients hospital census monitored via time series models; and (vii) quantified forecast performance. RESULTS: A consolidated forecast and monitoring report was produced weekly and proved to be an effective, vital source of information and guidance as the healthcare system navigated the inherent uncertainty of the pandemic. Forecasts provided accurate and precise information that informed critical decisions on resource planning, bed capacity and staffing management, and infection prevention strategies. CONCLUSIONS: In this paper, we have presented the framework used in our epidemiological forecast and monitoring program at Atrium Health, as well as provided recommendations for implementation by other healthcare systems and institutions to facilitate use in future pandemics.

A ratiometric substrate for rapid evaluation of transfer hydrogenation efficiency in solution.

A cyclometalated iridium(III) complex bearing a self-immolative quinolinium moiety was developed as a ratiometric substrate for transfer hydrogenation studies. This photoluminescent probe allowed the rapid screening of a variety of Ir catalysts using a microplate reader, offering a convenient method to assess activity using a minimum amount of catalyst sample.

Record-High Thermoelectric Performance in Al-Doped ZnO via Anderson Localization of Band Edge States.

Oxides are of interest for thermoelectrics due to their high thermal stability, chemical inertness, low cost, and eco-friendly constituting elements. Here, adopting a unique synthesis route via chemical co-precipitation at strongly alkaline conditions, one of the highest thermoelectric performances for ZnO ceramics ( P F max = $PF_{\text{max}} =$  21.5 µW cm-1 K-2 and z T max = $zT_{\text{max}} =$  0.5 at 1100 K in Zn 0.96 Al 0.04 O ${\rm Zn}_{0.96} {\rm Al}_{0.04}{\rm O}$ ) is achieved. These results are linked to a distinct modification of the electronic structure: charge carriers become trapped at the edge of the conduction band due to Anderson localization, evidenced by an anomalously low carrier mobility, and characteristic temperature and doping dependencies of charge transport. The bi-dimensional optimization of doping and carrier localization enable a simultaneous improvement of the Seebeck coefficient and electrical conductivity, opening a novel pathway to advance ZnO thermoelectrics.

MPCNN: A Novel Matrix Profile Approach for CNN-based Single Lead Sleep Apnea In Classification Problem.

Sleep apnea (SA) is a significant respiratory condition that poses a major global health challenge. Deep Learning (DL) has emerged as an efficient tool for the classification problem in electrocardiogram (ECG)-based SA diagnoses. Despite these advancements, most common conventional feature extractions derived from ECG signals in DL, such as R-peaks and RR intervals, may fail to capture crucial information encompassed within the complete ECG segments. In this study, we propose an innovative approach to address this diagnostic gap by delving deeper into the comprehensive segments of the ECG signal. The proposed methodology draws inspiration from Matrix Profile algorithms, which generate an Euclidean distance profile from fixed-length signal subsequences. From this, we derived the Min Distance Profile (MinDP), Max Distance Profile (MaxDP), and Mean Distance Profile (MeanDP) based on the minimum, maximum, and mean of the profile distances, respectively. To validate the effectiveness of our approach, we use the modified LeNet-5 architecture as the primary CNN model, along with two existing lightweight models, BAFNet and SE-MSCNN. Our experiment results on the PhysioNet Apnea-ECG dataset (70 overnight recordings), and the UCDDB dataset (25 overnight recordings) revealed that our new feature extraction method achieved per-segment accuracies of up to 92.11% and 81.25%, respectively. Moreover, using the PhysioNet data, we achieved a per-recording accuracy of 100% and yielded the highest correlation of 0.989 compared to state-of-the-art methods. By introducing a new feature extraction method based on distance relationships, we enhanced the performance of certain lightweight models in DL, showing potential for home sleep apnea test (HSAT) and SA detection in IoT devices. The source code for this work is made publicly available in GitHub: https://github.com/vinuni-vishc/MPCNN-Sleep-Apnea.

Lean body mass index is a marker of advanced tumor features in patients with hepatocellular carcinoma.

BACKGROUND: Obesity is an independent risk factor for the development of hepatocellular carcinoma (HCC) and may influence its outcomes. However, after diagnosis of HCC, like other malignancies, the obesity paradox may exist where higher body mass index (BMI) may in fact confer a survival benefit. This is frequently observed in patients with advanced HCC and cirrhosis, who often present late with advanced tumor features and cancer related weight loss. AIM: To explore the relationship between BMI and survival in patients with cirrhosis and HCC. METHODS: This is a retrospective cohort study of over 2500 patients diagnosed with HCC between 2009-2019 at two United States academic medical centers. Patient and tumor characteristics were extracted manually from medical records of each institutions' cancer registries. Patients were stratified according to BMI classes: < 25 kg/m2 (lean), 25-29.9 kg/m2 (overweight), and > 30 kg/m2 (obese). Patient and tumor characteristics were compared according to BMI classification. We performed an overall survival analysis using Kaplan Meier by the three BMI classes and after adjusting for Milan criteria. A multivariable Cox regression model was then used to assess known risk factors for survival in patients with cirrhosis and HCC. RESULTS: A total of 2548 patients with HCC were included in the analysis of which 11.2% (n = 286) were classified as non-cirrhotic. The three main BMI categories: Lean (n = 754), overweight (n = 861), and obese (n = 933) represented 29.6%, 33.8%, and 36.6% of the total population overall. Within each BMI class, the non-cirrhotic patients accounted for 15% (n = 100), 12% (n = 94), and 11% (n = 92), respectively. Underweight patients with a BMI < 18.5 kg/m2 (n = 52) were included in the lean cohort. Of the obese cohort, 42% (n = 396) had a BMI ≥ 35 kg/m2. Out of 2262 patients with cirrhosis and HCC, 654 (29%) were lean, 767 (34%) were overweight, and 841 (37%) were obese. The three BMI classes did not differ by age, MELD, or Child-Pugh class. Chronic hepatitis C was the dominant etiology in lean compared to the overweight and obese patients (71%, 62%, 49%, P < 0.001). Lean patients had significantly larger tumors compared to the other two BMI classes (5.1 vs 4.2 vs 4.2 cm, P < 0.001), were more likely outside Milan (56% vs 48% vs 47%, P < 0.001), and less likely to undergo transplantation (9% vs 18% vs 18%, P < 0.001). While both tumor size (P < 0.0001) and elevated alpha fetoprotein (P < 0.0001) were associated with worse survival by regression analysis, lean BMI was not (P = 0.36). CONCLUSION: Lean patients with cirrhosis and HCC present with larger tumors and are more often outside Milan criteria, reflecting cancer related cachexia from delayed diagnosis. Access to care for hepatitis C virus therapy and liver transplantation confer a survival benefit, but not overweight or obese BMI classifications.

Tumour size predicts risk of recurrence in tall cell subtype papillary thyroid carcinoma.

BACKGROUND: The tall cell subtype of papillary thyroid cancer (TCPTC) is the most common aggressive subtype and often treated aggressively. This approach may not be necessary in smaller tumours without adverse histological characteristics. METHODS: 97 patients with TCPTC defined as a height-to-width ratio of ≥3:1 and at least 30% tall cells were compared against 390 classical papillary thyroid carcinoma (CPTC) based on tumour size with recurrence free survival (RFS) as the primary outcome. RESULTS: TCPTC are more likely to present with adverse histological characteristics. In smaller tumours (<2 â€‹cm), only central lymph node metastasis (HR7.16 p â€‹= â€‹0.03) and multifocality (HR10.11 p â€‹= â€‹0.026) increased recurrence risk. In larger tumours, TCPTC histology (HR3.78 p â€‹= â€‹0.002), lymphovascular invasion (HR3.02 p â€‹= â€‹0.014) and central lymph node metastasis (HR3.24 p â€‹< â€‹0.001) significantly increased recurrence risk. CONCLUSION: TCPTC tumours <2 â€‹cm without central lymph node metastasis and multifocality are similar in risk of recurrence to classical PTC and could be managed with lobectomy.

Comparison of Clinical Features, Short-Term Outcome of Guillain-Barré Syndrome Between Adults and Children: A Retrospective Study in Vietnam.

BACKGROUND: Despite extensive research on Guillain-Barré syndrome (GBS) in adults and children, there is a lack of comparison regarding short-term outcomes in various age groups. Our study aims to elucidate the differences in clinical features and short-term outcomes in Vietnam. METHODS: After retrospective data collection, we compared clinical features in patients with GBS aged ≤16 years at Children's Hospital 2 and aged >16 years at University Medical Center Ho Chi Minh City from 2017 to 2021. A positive short-term outcome was recorded if patients had a GBS Disability Score of 0 to 2 at hospital discharge. RESULTS: We analyzed 109 adults (58.7% males; mean age 50.6 ± 17.7) and 111 children (58.6% males; mean age 7.2 ± 4.9). Comparable antecedent infection and immunization incidence in both groups were observed (35.8% vs 45.9%, P > 0.05). Pain and sensory disturbance were the most common onset symptom in adults (57.8%), whereas lower limb weakness predominated in children (61.3%). Ophthalmoplegia (18.3% vs 5.4%), pain, sensory disturbance (85.3% vs 67.6%), ataxia (33.0% vs 15.3%) were more prevalent in adults (P < 0.05). The axonal subtype was prominent in both adults (51.4%) and children (53.2%). Patients were classified into: classic GBS (49.5% and 68.5%), GBS variants (11.0% and 15.3%), classic Miller Fisher syndrome (MFS) (1.8% and 1.8%), MFS variants (2.8% and 0%), and GBS/MFS overlap (34.9% and 14.4%). Short-term outcomes did not significantly differ based on age. CONCLUSIONS: Age-related variations in clinical features were observed, but adults and children exhibited similar short-term functional outcomes.

Water adsorption on surfaces of calcium aluminosilicate crystal phase of stone wool: a DFT study.

Stone wool is widely used as an efficient thermal insulator within the construction industry; however, its performance can be significantly impacted by the presence of water vapor. By altering the material's characteristics and effective thermo-physical properties, water vapor can reduce overall efficacy in various environmental conditions. Therefore, understanding water adsorption on stone wool surfaces is crucial for optimizing insulation properties. Through the investigation of interaction between water molecules and calcium aluminosilicate (CAS) phase surfaces within stone wool using density functional theory (DFT), we can gain insight into underlying mechanisms governing water adsorption in these materials. This research aims to elucidate the molecular-level interaction between water molecules and CAS surfaces, which is essential for understanding fundamental properties that govern their adsorption process. Both dissociative and molecular adsorptions were investigated in this study. For molecular adsorption, the adsorption energy ranged from -  84 to -  113 kJ mol - 1 depending on surface orientation. A wider range of adsorption energy ( -  132 to -  236 kJ mol - 1 ) was observed for dissociative adsorption. Molecular adsorption was energetically favored on (010) surfaces while dissociative adsorption was most favorable on (111) surfaces. This DFT study provides valuable insights into the water adsorption behavior on low index surfaces of CAS phase in stone wool, which can be useful for designing effective strategies to manage moisture-related issues in construction materials. Based on these findings, additional research on the dynamics and kinetics of water adsorption and desorption processes of this thermal isolation material is suggested.

Morusacerane: A new gammacerane triterpenoid from the trunk of Morus Alba linn. with α-glucosidase inhibitory activity.

This phytochemistry investigation on the trunk of Morus alba L. resulted in the isolation of three triterpenoids, including a new gammacerane triterpenoid - morusacerane (1); along with two known compounds of betulinic acid (2) and ursolic acid (3). The structure elucidation was thoroughly conducted based on 1D, 2D-NMR and HRESIMS spectra, followed by a comparison with existing literatures. The evaluation on α-glucosidase inhibitory exhibited the great potential of the application of these isolated compounds in diabetes treatments. The results show that morusacerane (1), betulinic acid (2), and ursolic acid (3) demonstrate the strong inhibitory with the IC50 values of 106.1, 11.12, and 7.20 µM, respectively. All of these compounds interacted well with the allosteric site enzyme α-glucosidase MAL32 through H-bonds and hydrophobic interaction.

Phosphorylation-Driven Epichaperome Assembly: A Critical Regulator of Cellular Adaptability and Proliferation.

The intricate protein-chaperone network is vital for cellular function. Recent discoveries have unveiled the existence of specialized chaperone complexes called epichaperomes, protein assemblies orchestrating the reconfiguration of protein-protein interaction networks, enhancing cellular adaptability and proliferation. This study delves into the structural and regulatory aspects of epichaperomes, with a particular emphasis on the significance of post-translational modifications in shaping their formation and function. A central finding of this investigation is the identification of specific PTMs on HSP90, particularly at residues Ser226 and Ser255 situated within an intrinsically disordered region, as critical determinants in epichaperome assembly. Our data demonstrate that the phosphorylation of these serine residues enhances HSP90's interaction with other chaperones and co-chaperones, creating a microenvironment conducive to epichaperome formation. Furthermore, this study establishes a direct link between epichaperome function and cellular physiology, especially in contexts where robust proliferation and adaptive behavior are essential, such as cancer and stem cell maintenance. These findings not only provide mechanistic insights but also hold promise for the development of novel therapeutic strategies targeting chaperone complexes in diseases characterized by epichaperome dysregulation, bridging the gap between fundamental research and precision medicine.

Utility of multimodal longitudinal imaging data for dynamic prediction of cardiovascular and renal disease: the CARDIA study.

Background: Medical examinations contain repeatedly measured data from multiple visits, including imaging variables collected from different modalities. However, the utility of such data for the prediction of time-to-event is unknown, and only a fraction of the data is typically used for risk prediction. We hypothesized that multimodal longitudinal imaging data could improve dynamic disease prognosis of cardiovascular and renal disease (CVRD). Methods: In a multi-centered cohort of 5,114 CARDIA participants, we included 166 longitudinal imaging variables from five imaging modalities: Echocardiography (Echo), Cardiac and Abdominal Computed Tomography (CT), Dual-Energy x-ray Absorptiometry (DEXA), Brain Magnetic Resonance Imaging (MRI) collected from young adulthood to mid-life over 30 years (1985-2016) to perform dynamic survival analysis of CVRD events using machine learning dynamic survival analysis (Dynamic-DeepHit, LTRCforest, and Extended Cox for Time-varying Covariates). Risk probabilities were continuously updated as new data were collected. Model performance was assessed using integrated AUC and C-index and compared to traditional risk factors. Results: Longitudinal imaging data, even when being irregularly collected with high missing rates, improved CVRD dynamic prediction (0.03 in integrated AUC, up to 0.05 in C-index compared to traditional risk factors; best model's C-index = 0.80-0.83 up to 20 years from baseline) from young adulthood followed up to midlife. Among imaging variables, Echo and CT variables contributed significantly to improved risk estimation. Echo measured in early adulthood predicted midlife CVRD risks almost as well as Echo measured 10-15 years later (0.01 C-index difference). The most recent CT exam provided the most accurate prediction for short-term risk estimation. Brain MRI markers provided additional information from cardiac Echo and CT variables that led to a slightly improved prediction. Conclusions: Longitudinal multimodal imaging data readily collected from follow-up exams can improve CVRD dynamic prediction. Echocardiography measured early can provide a good long-term risk estimation, while CT/calcium scoring variables carry atherosclerotic signatures that benefit more immediate risk assessment starting in middle-age.

A new species of Typhonium (Araceae) from Vietnam.

Typhoniumobtusum is described as a new species endemic to Vietnam. It is unique in the genus in having an oblong-elliptic spathe limb with an obtuse apex and yellowish-greenish filiform staminodes with a down-curved acumen. The ecology, distribution and assessment of the conservation status of the new taxon, as well as a key to all known Typhonium species in Vietnam, are provided.

Homogeneous crystallization and buried interface passivation for perovskite tandem solar modules.

Scalable fabrication of all-perovskite tandem solar cells is challenging because the narrow-bandgap subcells made of mixed lead-tin (Pb-Sn) perovskite films suffer from nonuniform crystallization and inferior buried perovskite interfaces. We used a dopant from Good's list of biochemical buffers, aminoacetamide hydrochloride, to homogenize perovskite crystallization and used it to extend the processing window for blade-coating Pb-Sn perovskite films and to selectively passivate defects at the buried perovskite interface. The resulting all-perovskite tandem solar module exhibited a certified power conversion efficiency of 24.5% with an aperture area of 20.25 square centimeters.

Discovery of the male of Okinawepipona yty Nguyen, 2018 (Hymenoptera: Vespidae: Eumeninae) from Vietnam.

The male of Okinawepipona yty Nguyen, 2018 is described and illustrated for the first time, together with its genitalia, based on specimens from Y Ty, Lao Cai, Vietnam. In addition, the male genitalia of O. curcipunctura Nguyen & Xu, 2014 is also described for the first time. Based on these descriptions, a discussion is provided regarding the male genitalia of eumenine wasps in general.

A close-up shot of protein-protein docking, from experiment to theory and reverse with the PROTAC performers.

PROTACs (Proteolysis Targeting Chimeras), heterobifunctional molecules, exhibit selectivity in degrading target proteins through E3 ubiquitin ligases. Designing effective PROTACs requires a deep understanding of the intricate binding interactions in the ternary complex (POI/PROTAC/E3 ligase), crucial for efficient target protein degradation. To address this challenge, we introduce a novel computational virtual screening method that considers essential amino acid interactions between the protein of interest and the chosen E3 ligase. This approach enhances accuracy and reliability, facilitating the strategic development of potent PROTACs. Utilizing a crystallized model of the VHL:PROTAC:SMARCA2BD ternary complex (PDB: 7Z6L), we assessed the effectiveness of our method. Our study reveals that increasing the number of essential restraints between the two proteins reduces the generated docking poses, leading to closer alignment with the experimental ternary complex. Specifically, utilizing three restraints showed the closest resemblance to the published complex, highlighting crucial interactions such as an H-bond between A:Gln 89 and B:Asn 67, along with two hydrophobic interactions: A:Gly 22 with B:Arg 69 and A:Glu 37 with B:Pro 99. This resulted in a significant decrease in the mean RMSD value from 31.8 and 31.0 Å to 24.4 Å, respectively. This underscores the importance of incorporating multiple essential restraints to enhance docking accuracy. Building on this progress, we introduce a systematic approach to design potential PROTACs between the Estrogen receptor and the E3 ligase, utilizing bridging intermediates with 4, 6, or 7 carbon atoms. By providing a more accurate and efficient means of identifying optimal PROTAC candidates, this approach has the potential to accelerate the development of targeted therapies and reduce the time and costs associated with drug discovery.Communicated by Ramaswamy H. Sarma.

Emerging horizons and prospects of polysaccharide-constructed gels in the realm of wound healing.

Polysaccharides, with the abundant availability, biodegradability, and inherent safety, offer a vast array of promising applications. Leveraging the remarkable attributes of polysaccharides, biomimetic and multifunctional hydrogels have emerged as a compelling avenue for efficacious wound dressing. The gels emulate the innate extracellular biomatrix as well as foster cellular proliferation. The distinctive structural compositions and profusion of functional groups within polysaccharides confer excellent physical/chemical traits as well as distinct restorative involvements. Gels crafted from polysaccharide matrixes serve as a robust defense against bacterial threats, effectively shielding wounds from harm. This comprehensive review delves into wound physiology, accentuating the significance of numerous polysaccharide-based gels in the wound healing context. The discourse encompasses an exploration of polysaccharide hydrogels tailored for diverse wound types, along with an examination of various therapeutic agents encapsulated within hydrogels to facilitate wound repair, incorporating recent patent developments. Within the scope of this manuscript, the perspective of these captivating gels for promoting optimal healing of wounds is vividly depicted. Nevertheless, the pursuit of knowledge remains ongoing, as further research is warranted to bioengineer progressive polysaccharide gels imbued with adaptable features. Such endeavors hold the promise of unlocking substantial potential within the realm of wound healing, propelling us toward multifaceted and sophisticated solutions.

STEM in situ thermal wave observations for investigating thermal diffusivity in nanoscale materials and devices.

Practical techniques to identify heat routes at the nanoscale are required for the thermal control of microelectronic, thermoelectric, and photonic devices. Nanoscale thermometry using various approaches has been extensively investigated, yet a reliable method has not been finalized. We developed an original technique using thermal waves induced by a pulsed convergent electron beam in a scanning transmission electron microscopy (STEM) mode at room temperature. By quantifying the relative phase delay at each irradiated position, we demonstrate the heat transport within various samples with a spatial resolution of ~10 nm and a temperature resolution of 0.01 K. Phonon-surface scatterings were quantitatively confirmed due to the suppression of thermal diffusivity. The phonon-grain boundary scatterings and ballistic phonon transport near the pulsed convergent electron beam were also visualized.

Comparison between U-shaped structural deep learning models to detect landslide traces.

Landslides endanger lives and public infrastructure in mountainous areas. Monitoring landslide traces in real-time is difficult for scientists, sometimes costly and risky because of the harsh terrain and instability. Nowadays, modern technology may be able to identify landslide-prone locations and inform locals for hours or days when the weather worsens. This study aims to propose indicators to detect landslide traces on the fields and remote sensing images; build deep learning (DL) models to identify landslides from Sentinel-2 images automatically; and apply DL-trained models to detect this natural hazard in some particular areas of Vietnam. Nine DL models were trained based on three U-shaped architectures, including U-Net, U2-Net, and U-Net3+, and three options of input sizes. The multi-temporal Sentinel-2 images were chosen as input data for training all models. As a result, the U-Net, using an input image size of 32 × 32 and a performance of 97 % with a loss function of 0.01, can detect typical landslide traces in Vietnam. Meanwhile, the U-Net (64 × 64) can detect more considerable landslide traces. Based on multi-temporal remote sensing data, a different case study in Vietnam was chosen to see landslide traces over time based on the trained U-Net (32 × 32) model. The trained model allows mountain managers to track landslide occurrences during wet seasons. Thus, landslide incidents distant from residential areas may be discovered early to warn of flash floods.

Self-Organized Plasmonic Nanowire Arrays Coated with Ultrathin TiO2 Films for Photoelectrochemical Energy Storage.

The strategic field of renewable energy production and storage requires novel nanoscale platforms that can feature competitive solar energy conversion properties. Photochemical reactions that promote energy storage, such as water splitting and oxygen-hydrogen evolution reactions, play a crucial role in this context. Here, we demonstrate a novel photoelectrochemical device based on large-area (cm2) self-organized Au nanowire (NW) arrays, uniformly coated with ultrathin TiO2 films. The NW arrays act both as transparent nanoelectrodes and as a plasmonic metasurface that resonantly enhances the very weak visible photocurrent generated by a prototype photoelectrochemical oxygen evolution reaction. We demonstrate a polarization-sensitive plasmon-enhanced photocurrent that reaches a gain of about 3.8 in the visible spectral range. This highlights the potential of our novel nanopatterned plasmonic platform in photochemistry and energy storage.

A retrospective study of endogenous endophthalmitis-related pyogenic liver abscess: An increasing complication in North Vietnam.

Introduction: Endogenous endophthalmitis-related Klebsiella pyogenic liver abscess is a rare complication of metastatic infection. In most cases, visual acuity results are often impaired, even blind, and even with aggressive treatment with topical antibiotics, the final results are unsatisfactory. The objective of this study is to retrospectively based on medical records to describe clinical features, risk factors, and visual outcomes of patients with endogenous endophthalmitis-related pyogenic liver abscesses. Methods: We reported a case series of 12 endogenous endophthalmitis-related pyogenic liver abscess patients from March 2021 to 2023. All cases of endogenous endophthalmitis were diagnosed at admission or during the hospital stay. Results: From the medical records of 588 pyogenic liver abscess patients, we found 12 cases of endogenous endophthalmitis with 2.0%. The result showed a mean age of 61.5 ± 12.0 (41-78), diabetes mellitus (7 of 12), right lobe (7 of 12), single abscess (9 of 12), and the mean largest abscess diameter of 5.8 ± 1.7 cm (3.3-9). All patients had ocular symptoms such as eye pain (9 of 12), pus discharge (3 of 12), hypopyon (1 of 12), swollen eyelids (2 of 12), and corneal edema (2 of 12), pyogenic liver abscess before endogenous endophthalmitis (10 of 12), the median interval between endogenous endophthalmitis and pyogenic liver abscess 6.1 ± 1.9 days, ocular symptoms before diagnosis endogenous endophthalmitis 4.4 ± 2.3 days. All affected eyes were injected intravitreously with ceftazidime, amikacin, and vancomycin. Two patients underwent evisceration. Conclusions: Endogenous endophthalmitis has permanent morbidity, reducing visual acuity, poor quality of life, and lacks the warning signs, so it is essential for early detection of symptoms and referral to ophthalmologists.