A chemometric and ingestion hazard prediction study of groundwater in proximity to the Bandhwari landfill site, Gurugram, India.

Groundwater contamination due to the leaching of harmful pollutants such as heavy metals, xenobiotic compounds, and other inorganic compounds from solid waste dumping sites has become a major health concern in recent times. Therefore, to assess the effects of the Bandhwari landfill site, groundwater samples from the surrounding region of the dumping site were collected and analyzed for heavy metals and physicochemical properties. The total dissolved solids (TDS) of 67% of samples exceeded the Bureau of Indian Standards (BIS) permissible limits which makes it unfit for drinking purposes. The groundwater samples were also analyzed for iron (Fe), lead (Pb), zinc (Zn), nickel (Ni), copper (Cu), cadmium (Cd), and chromium (Cr) concentrations and results of heavy metal concentration in the groundwater around the Bandhwari landfill follow the concentration trend of Pb > Cd > Ni > Cu > Zn > Fe > Cr. Risk assessment of consumers' health was done using target hazard quotient calculations which were less than unity (threshold value of <1), indicating that heavy metal concentrations do not pose any serious health effect according to total hazard quotient values. The results of the study made it evident that groundwater is not suitable for drinking purposes due to excess values of water quality parameters but poses no risk due to studied metal concentrations.

A comprehensive physico-chemical quality and heavy metal health risk assessment study for phreatic water sources in Narora Atomic Power Station region, Narora, India.

An investigation of water quality and heavy metal distribution in the groundwater samples collected from the vicinity of Narora Atomic Power Station (NAPS), Narora, India, was conducted for the metals including Cu, Zn, Ni, Co, Cd, Pb, and Fe. A total of 16 water quality parameters were measured for all the groundwater samples, and TDS, TH, Mg2+, Ca2+, F-, and turbidity were found to be on the higher side in comparison to the prescribed limits of Indian standards. Geometrical mean concentrations for these heavy metals were found to be 0.049, 0.213, 0.23, 0.135, 0.017, 0.061, and BDL for Cu, Fe, Zn, Pb, Cd, Co, and Ni, respectively. Pb and Cd were more than the permissible limits (0.01 mg/L for Pb and 0.003 for Cd) prescribed for safe drinking water while Cu and Fe were exceeding the permissible limits of 0.05 mg/L and 0.3 mg/L in 32% and 36% samples, respectively. Health risk assessment was done by calculating total hazard quotient (THQ), and the values for all the metals were below the threshold value of 1.0 beyond which they may pose a significant risk.

Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation.

BACKGROUND: COVID-19 has infected millions of people worldwide and is responsible for several hundred thousand fatalities. The COVID-19 pandemic has necessitated thoughtful resource allocation and early identification of high-risk patients. However, effective methods to meet these needs are lacking. OBJECTIVE: The aims of this study were to analyze the electronic health records (EHRs) of patients who tested positive for COVID-19 and were admitted to hospitals in the Mount Sinai Health System in New York City; to develop machine learning models for making predictions about the hospital course of the patients over clinically meaningful time horizons based on patient characteristics at admission; and to assess the performance of these models at multiple hospitals and time points. METHODS: We used Extreme Gradient Boosting (XGBoost) and baseline comparator models to predict in-hospital mortality and critical events at time windows of 3, 5, 7, and 10 days from admission. Our study population included harmonized EHR data from five hospitals in New York City for 4098 COVID-19-positive patients admitted from March 15 to May 22, 2020. The models were first trained on patients from a single hospital (n=1514) before or on May 1, externally validated on patients from four other hospitals (n=2201) before or on May 1, and prospectively validated on all patients after May 1 (n=383). Finally, we established model interpretability to identify and rank variables that drive model predictions. RESULTS: Upon cross-validation, the XGBoost classifier outperformed baseline models, with an area under the receiver operating characteristic curve (AUC-ROC) for mortality of 0.89 at 3 days, 0.85 at 5 and 7 days, and 0.84 at 10 days. XGBoost also performed well for critical event prediction, with an AUC-ROC of 0.80 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. In external validation, XGBoost achieved an AUC-ROC of 0.88 at 3 days, 0.86 at 5 days, 0.86 at 7 days, and 0.84 at 10 days for mortality prediction. Similarly, the unimputed XGBoost model achieved an AUC-ROC of 0.78 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. Trends in performance on prospective validation sets were similar. At 7 days, acute kidney injury on admission, elevated LDH, tachypnea, and hyperglycemia were the strongest drivers of critical event prediction, while higher age, anion gap, and C-reactive protein were the strongest drivers of mortality prediction. CONCLUSIONS: We externally and prospectively trained and validated machine learning models for mortality and critical events for patients with COVID-19 at different time horizons. These models identified at-risk patients and uncovered underlying relationships that predicted outcomes.

Effect of scrotal bifurcation on breeding soundness traits in Beetal bucks during summer season.

Relationship of scrotal bifurcation or splitness with breeding soundness traits was investigated in 15 Beetal bucks (17-20 months of age and 48.72 ± 1.57 kg mean BW). Breeding soundness traits of conjoined/unsplit (n = 6) scrotal bucks was compared with split (n = 9) scrotal bucks having lengthwise > 1 in. bifurcation. Two consecutive semen ejaculations per buck were collected at monthly interval during summer season (April to June 2018) using intact buck as teaser and sexual behavior was simultaneously recorded. Scrotal morphometry parameters, i.e., scrotal circumference, scrotal volume, scrotal skin thickness, testis length, width, and thickness were also recorded. Bucks with split scrotum had relatively more scrotal dimensions (scrotal circumference (P < 0.01), scrotal volume (P < 0.01), testis length (P < 0.01)) than conjoined scrotal bucks. Among various semen attributes, semen volume of first ejaculate (P < 0.01), second ejaculate (P < 0.05), mean semen volume (P < 0.01), total sperm count of first ejaculate, and mean sperm count of both ejaculates were more (P < 0.01) in split scrotal bucks. However, scrotal bifurcation had no influence on sexual behavior of bucks. It is concluded that Beetal bucks with split scrotum had relatively better breeding efficiency traits than conjoined scrotal bucks.

Spontaneous atraumatic rupture of the urinary bladder following alcohol intoxication: A rare case report.

Key Clinical Message: Consideration of spontaneous urinary bladder rupture in the differential diagnosis of acute abdominal pain for alcohol-abusing patients is crucial for ensuring timely surgical intervention and preventing life-threatening complications due to its high associated morbidity and mortality. Abstract: Spontaneous rupture of the urinary bladder (SRUB) is a rare but critical urological emergency, typically associated with malignancy, neurogenic dysfunction, or previous radiation therapy. Here, we present a unique case of SRUB in a 65-year-old chronic alcoholic male who presented with acute lower abdominal pain following heavy alcohol consumption. Initial evaluations revealed leukocytosis, elevated serum creatinine levels, and ultrasound findings suggestive of bladder rupture. Computed tomography confirmed the diagnosis, indicating an intraperitoneal rupture with associated hematoma. Immediate surgical repair was performed, leading to a successful outcome. This case underscores the importance of considering SRUB in patients with acute abdominal pain, especially in the context of alcohol intoxication, and highlights the diagnostic and therapeutic challenges associated with this condition. Early recognition and intervention are crucial to prevent life-threatening complications associated with urinary bladder rupture.

Proportion of thyroid cancer and other cancers in the democratic republic of Congo.

BACKGROUND: Cancer diagnosis is increasing around the world and in the Democratic Republic of the Congo (DRC). The proportion of thyroid cancer has increased over the past three decades. There are very few studies on cancer epidemiology, and in particular on thyroid cancer in the DRC. AIM: To establish the most recent proportion of thyroid cancer in the DRC compared to other cancers. METHODS: This is a retrospective and descriptive study of 6106 consecutive cancer cases listed in the pathological registers of 4 Laboratories in the city of Kinshasa. This study included all cancer cases recorded in the registers between 2005 and 2019. RESULTS: From a sample of 6106 patients, including all cancer types, 68.3% cases were female and 31.7% were male. Breast and cervical cancer were the most common types of cancer in women and, prostate and skin cancer were the most common types in men. Thyroid cancer was sixth in proportion in women and eleventh in men compared to all cancers. Papillary carcinoma was the most common of thyroid cancers. Rare cancers such as anaplastic and medullary thyroid carcinomas had a proportion of 7% and 2%, respectively. CONCLUSION: Newer diagnostic tools led to a surge in cancer diagnoses in the DRC. Thyroid cancer has more than doubled its proportion over the last several decades in the country.

Bladder and Bowel Dysfunction Network: Improving the Management of Pediatric Bladder and Bowel Dysfunction.

Lower urinary tract symptoms with constipation characterize bladder and bowel dysfunction (BBD). Due to high referral volumes to hospital pediatric urology clinics and time-consuming appointments, wait times are prolonged. Initial management consists of behavioral modification strategies that could be accomplished by community pediatricians. We aimed to create a network of community pediatricians trained in BBD (BBDN) management and assess its impact on care. METHODS: We distributed a survey to pediatricians, and those interested attended training consisting of lectures and clinical shadowing. Patients referred to a hospital pediatric urology clinic were triaged to the BBDN and completed the dysfunctional voiding symptom score and satisfaction surveys at baseline and follow-up. The Bristol stool chart was used to assess constipation. Results were compared between BBDN and hospital clinic patients. RESULTS: Surveyed pediatricians (n = 100) most commonly managed BBD with PEG3350 and dietary changes and were less likely to recommend bladder retraining strategies. Baseline characteristics were similar in BBDN (n = 100) and hospital clinic patients (n = 23). Both groups had similar improvements in dysfunctional voiding symptom score from baseline to follow-up (10.1 ± 4.2 to 5.6 ± 3.3, P = 0.01, versus 10.1 ± 4.2 to 7.8 ± 4.5, P = 0.02). BBDN patients waited less time for their follow-up visit with 56 (28-70) days versus 94.5 (85-109) days for hospital clinic patients (P < 0.001). Both groups demonstrated high familial satisfaction. CONCLUSIONS: Community pediatricians may require more knowledge of management strategies for BBD. Our pilot study demonstrates that implementing a BBDN is feasible, results in shorter wait times, and similar improvement in symptoms and patient satisfaction than a hospital pediatric urology clinic.

Independent component analysis-based multifiber streamline tractography of the human brain.

An independent component analysis-based approach has been developed to estimate the orientations of two or three crossing fibers in a voxel to conduct human brain streamline tractography from diffusion data acquired along 25 gradient directions at a b-value of 1000 sec/mm(2) . The approach relies on unmixing signals from fibers mixed within, and spread over, a small cluster of 11 voxels. Simulation studies of diffusion data for two or three crossing fibers at signal-to-noise ratios of 15 and 30 suggest the accuracy to determine interfiber angles with independent component analysis is similar to that attained by a gaussian mixture and other multicompartmental models but at two orders of magnitude faster computational speed. Compared to previous multicompartmental models, independent component analysis visually shows good recovery of fiber orientations and tracts in the crossing region of commonly available orthogonal and 60° phantom diffusion datasets. A 3T MRI human studies show that in contrast to conventional streamline tractography and a multicompartment model, independent component analysis shows better recovery of the continuity of fronto-occipital tracts and cingulum from regions where these tracts are mixed with corpus callosum and other pathways.

Retrospective cohort study of clinical characteristics of 2199 hospitalised patients with COVID-19 in New York City.

OBJECTIVE: The COVID-19 pandemic is a global public health crisis, with over 33 million cases and 999 000 deaths worldwide. Data are needed regarding the clinical course of hospitalised patients, particularly in the USA. We aimed to compare clinical characteristic of patients with COVID-19 who had in-hospital mortality with those who were discharged alive. DESIGN: Demographic, clinical and outcomes data for patients admitted to five Mount Sinai Health System hospitals with confirmed COVID-19 between 27 February and 2 April 2020 were identified through institutional electronic health records. We performed a retrospective comparative analysis of patients who had in-hospital mortality or were discharged alive. SETTING: All patients were admitted to the Mount Sinai Health System, a large quaternary care urban hospital system. PARTICIPANTS: Participants over the age of 18 years were included. PRIMARY OUTCOMES: We investigated in-hospital mortality during the study period. RESULTS: A total of 2199 patients with COVID-19 were hospitalised during the study period. As of 2 April, 1121 (51%) patients remained hospitalised, and 1078 (49%) completed their hospital course. Of the latter, the overall mortality was 29%, and 36% required intensive care. The median age was 65 years overall and 75 years in those who died. Pre-existing conditions were present in 65% of those who died and 46% of those discharged. In those who died, the admission median lymphocyte percentage was 11.7%, D-dimer was 2.4 µg/mL, C reactive protein was 162 mg/L and procalcitonin was 0.44 ng/mL. In those discharged, the admission median lymphocyte percentage was 16.6%, D-dimer was 0.93 µg/mL, C reactive protein was 79 mg/L and procalcitonin was 0.09 ng/mL. CONCLUSIONS: In our cohort of hospitalised patients, requirement of intensive care and mortality were high. Patients who died typically had more pre-existing conditions and greater perturbations in inflammatory markers as compared with those who were discharged.

Acute Kidney Injury in Hospitalized Patients with COVID-19.

IMPORTANCE: Preliminary reports indicate that acute kidney injury (AKI) is common in coronavirus disease (COVID)-19 patients and is associated with worse outcomes. AKI in hospitalized COVID-19 patients in the United States is not well-described. OBJECTIVE: To provide information about frequency, outcomes and recovery associated with AKI and dialysis in hospitalized COVID-19 patients. DESIGN: Observational, retrospective study. SETTING: Admitted to hospital between February 27 and April 15, 2020. PARTICIPANTS: Patients aged ≥18 years with laboratory confirmed COVID-19 Exposures: AKI (peak serum creatinine increase of 0.3 mg/dL or 50% above baseline). Main Outcomes and Measures: Frequency of AKI and dialysis requirement, AKI recovery, and adjusted odds ratios (aOR) with mortality. We also trained and tested a machine learning model for predicting dialysis requirement with independent validation. RESULTS: A total of 3,235 hospitalized patients were diagnosed with COVID-19. AKI occurred in 1406 (46%) patients overall and 280 (20%) with AKI required renal replacement therapy. The incidence of AKI (admission plus new cases) in patients admitted to the intensive care unit was 68% (553 of 815). In the entire cohort, the proportion with stages 1, 2, and 3 AKI were 35%, 20%, 45%, respectively. In those needing intensive care, the respective proportions were 20%, 17%, 63%, and 34% received acute renal replacement therapy. Independent predictors of severe AKI were chronic kidney disease, systolic blood pressure, and potassium at baseline. In-hospital mortality in patients with AKI was 41% overall and 52% in intensive care. The aOR for mortality associated with AKI was 9.6 (95% CI 7.4-12.3) overall and 20.9 (95% CI 11.7-37.3) in patients receiving intensive care. 56% of patients with AKI who were discharged alive recovered kidney function back to baseline. The area under the curve (AUC) for the machine learned predictive model using baseline features for dialysis requirement was 0.79 in a validation test. CONCLUSIONS AND RELEVANCE: AKI is common in patients hospitalized with COVID-19, associated with worse mortality, and the majority of patients that survive do not recover kidney function. A machine-learned model using admission features had good performance for dialysis prediction and could be used for resource allocation.

Clinical Characteristics of Hospitalized Covid-19 Patients in New York City.

BACKGROUND: The coronavirus 2019 (Covid-19) pandemic is a global public health crisis, with over 1.6 million cases and 95,000 deaths worldwide. Data are needed regarding the clinical course of hospitalized patients, particularly in the United States. METHODS: Demographic, clinical, and outcomes data for patients admitted to five Mount Sinai Health System hospitals with confirmed Covid-19 between February 27 and April 2, 2020 were identified through institutional electronic health records. We conducted a descriptive study of patients who had in-hospital mortality or were discharged alive. RESULTS: A total of 2,199 patients with Covid-19 were hospitalized during the study period. As of April 2 nd , 1,121 (51%) patients remained hospitalized, and 1,078 (49%) completed their hospital course. Of the latter, the overall mortality was 29%, and 36% required intensive care. The median age was 65 years overall and 75 years in those who died. Pre-existing conditions were present in 65% of those who died and 46% of those discharged. In those who died, the admission median lymphocyte percentage was 11.7%, D-dimer was 2.4 ug/ml, C-reactive protein was 162 mg/L, and procalcitonin was 0.44 ng/mL. In those discharged, the admission median lymphocyte percentage was 16.6%, D-dimer was 0.93 ug/ml, C-reactive protein was 79 mg/L, and procalcitonin was 0.09 ng/mL. CONCLUSIONS: This is the largest and most diverse case series of hospitalized patients with Covid-19 in the United States to date. Requirement of intensive care and mortality were high. Patients who died typically had pre-existing conditions and severe perturbations in inflammatory markers.

Vibrotactile activation of the auditory cortices in deaf versus hearing adults.

Neuroplastic changes in auditory cortex as a result of lifelong perceptual experience were investigated. Adults with early-onset deafness and long-term hearing aid experience were hypothesized to have undergone auditory cortex plasticity due to somatosensory stimulation. Vibrations were presented on the hand of deaf and normal-hearing participants during functional MRI. Vibration stimuli were derived from speech or were a fixed frequency. Higher, more widespread activity was observed within auditory cortical regions of the deaf participants for both stimulus types. Life-long somatosensory stimulation due to hearing aid use could explain the greater activity observed with deaf participants.

Soft tissue differentiation using multiband signatures of high resolution ultrasonic transmission tomography.

In this paper, we are interested in soft tissue differentiation by multiband images obtained from the High-Resolution Ultrasonic Transmission Tomography (HUTT) system using a spectral target detection method based on constrained energy minimization (CEM). We have developed a new tissue differentiation method (called "CEM filter bank") consisting of multiple CEM filters specially designed for detecting multiple types of tissues. Statistical inference on the output of the CEM filter bank is used to make a decision based on the maximum statistical significance rather than the magnitude of each CEM filter output. We test and validate this method through three-dimensional interphantom/intraphantom soft tissue classification where target profiles obtained from an arbitrary single slice are used for differentiation over multiple other tomographic slices. The performance of the proposed classifier is assessed using receiver operating characteristic analysis. We also apply our method to classify tiny structures inside a bovine kidney and sheep kidneys. Using the proposed method we can detect physical objects and biological tissues such as styrofoam balls, chicken tissue, calyces, and vessel-duct successfully.

Visual speech perception without primary auditory cortex activation.

Speech perception is conventionally thought to be an auditory function, but humans often use their eyes to perceive speech. We investigated whether visual speech perception depends on processing by the primary auditory cortex in hearing adults. In a functional magnetic resonance imaging experiment, a pulse-tone was presented contrasted with gradient noise. During the same session, a silent video of a talker saying isolated words was presented contrasted with a still face. Visual speech activated the superior temporal gyrus anterior, posterior, and lateral to the primary auditory cortex, but not the region of the primary auditory cortex. These results suggest that visual speech perception is not critically dependent on the region of primary auditory cortex.

Functional magnetic resonance imaging for brain mapping in neurosurgery.

One of the most pertinent applications of the principle primum non nocere (first do no harm) is in the optimization of neurosurgical procedures for patients with resectable lesions. The gold standard for identifying eloquent areas of the brain to be avoided in resections is direct cortical stimulation and somatosensory evoked potential monitoring, which is itself an invasive, cumbersome and difficult technique for mapping these areas. Functional magnetic resonance imaging shows great promise as a viable noninvasive alternative to invasive mapping as well as significant current clinical utility in cases in which it cannot yet fully supplant cortical stimulation methods. Ongoing work is directed toward overcoming technical limitations, improved mapping of complex functions such as language and memory, and mapping of white matter tracts.

Novel diffusion tensor imaging methodology to detect and quantify injured regions and affected brain pathways in traumatic brain injury.

PURPOSE: To develop and apply diffusion tensor imaging (DTI)-based normalization methodology for the detection and quantification of sites of traumatic brain injury (TBI) and the impact of injury along specific brain pathways in (a) individual TBI subjects and (b) a TBI group. MATERIALS AND METHODS: Normalized DTI tractography was conducted in the native space of 12 TBI and 10 age-matched control subjects using the same number of seeds in each subject, distributed at anatomically equivalent locations. Whole-brain tracts from the control group were mapped onto the head of each TBI subject. Differences in the fractional anisotropy (FA) maps between each TBI subject and the control group were computed in a common space using a t test, transformed back to the individual TBI subject's head space, and thresholded to form regions of interest (ROIs) that were used to sort tracts from the control group and the individual TBI subject. Tract counts for a given ROI in each TBI subject were compared to group mean for the same ROI to quantify the impact of injury along affected pathways. The same procedure was used to compare the TBI group to the control group in a common space. RESULTS: Sites of injury within individual TBI subjects and affected pathways included hippocampal/fornix, inferior fronto-occipital, inferior longitudinal fasciculus, corpus callosum (genu and splenium), cortico-spinal tracts and the uncinate fasciculus. Most of these regions were also detected in the group study. CONCLUSIONS: The DTI normalization methodology presented here enables automatic delineation of ROIs within the heads of individual subjects (or in a group). These ROIs not only localize and quantify the extent of injury, but also quantify the impact of injury on affected pathways in an individual or in a group of TBI subjects.

Recovery of multiple fibers per voxel by ICA in DTI tractography.

Relying on a rank-2 tensor model for diffusion within a voxel, conventional streamline tractography utilizes principal component analysis (PCA) to detect the orientation of a single fiber within a voxel. When more than one fibers or tracts intersect within a voxel, the PCA estimated orientation lies somewhere in-between the multiple fiber directions and is obviously an incomplete and incorrect representation of the underlying fibers in the voxel. This paper investigates the applicability of independent component analysis (ICA) to estimate individual tensors when multiple tensors corresponding to multiple intersecting fibers are present within a voxel. After establishing non-Gaussianity of the diffusion tensor imaging (DTI) signals, which is a pre-requisite for ICA, a Monte Carlo simulation study is conducted to show the accuracy of recovering the orientations of two or three tensors (fibers) mixed within a voxel. It is concluded that the principal eigen vectors but not the eigen values of multiple fibers are recoverable by conventional fast ICA.

Acceleration of fiber tracking in DTI tractography by reconfigurable computer hardware.

Diffusion Tensor Imaging (DTI) tractography is a computationally intensive procedure. The most time consuming operation is the tracking of fibers from every voxel in the scanned volume. Fiber tracking can be accelerated significantly by use of reconfigurable hardware, such as Field Programmable Gate Arrays (FPGAs), which can track fibers at very high speed by exploiting the flexibility, parallelism and high on-chip bandwidth. Such acceleration has the potential to lead to realtime tractography. In this paper we isolate key kernels within the tracking step and through a simulation study, analyze a specific FPGA architecture comprising deeply pipelined kernel chains running in parallel. Our results suggest that the FPGA based computer architecture could achieve a two orders of magnitude speed-up in the fiber-tracking algorithm over an optimized C-code.

Correlation between BOLD-fMRI and EEG signal changes in response to visual stimulus frequency in humans.

The correlation between signals acquired using electroencephalography (EEG) and fMRI was investigated in humans during visual stimulation. Evoked potential EEG and BOLD fMRI data were acquired independently under similar conditions from eight subjects during stimulation by a checkerboard flashed at frequencies ranging from 2-12 Hz. The results indicate highly correlated changes in the strength of the EEG signal averaged over two occipital electrodes and the BOLD signal within the occipital lobe as a function of flash frequency for 7/8 subjects (average linear correlation coefficient of 0.76). Both signals peaked at approximately 8 Hz. For one subject the correlation coefficient was 0.20; the EEG signal peaked at 6 Hz and the BOLD signal peaked at 10 Hz. Overall, the EEG and BOLD signals, each averaged over 40-sec stimulation periods, appear to be coupled linearly during visual stimulation by a flashing checkerboard.